Continuously monitoring and updating mortgage ready data

ABSTRACT

A system and computer-implemented method for continuously updating information about one or more of a customer approved for a mortgage and a real estate property identified as mortgage ready using computer technology and/or machine learning algorithms or artificial intelligence. The method includes monitoring information corresponding to one or more of the customer or the real estate property; identifying new information about one or more of the customer or the real estate property; updating a computer file and/or memory location/address to include the new information about one or more of the customer or the real estate property; and recalculating one or more of the amount in which the customer is approved for the mortgage or the appraisal value of the real estate property based upon one or more of new information received and the updated information from the computer file and/or memory location/address.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent ApplicationNo. 62/504,328, filed on May 10, 2017, and entitled “System and Methodof Utilizing Blockchain Technology to Approve and Update DynamicMortgage Applications,” U.S. Provisional Patent Application No.62/514,470, filed on Jun. 2, 2017, and entitled “System and Method ofUtilizing Blockchain Technology to Approve and Update Dynamic MortgageApplications,” U.S. Provisional Patent Application No. 62/535,018, filedJul. 20, 2017, and entitled “System and Method of Approving and UpdatingDynamic Mortgage Applications,” and U.S. Provisional Patent ApplicationNo. 62/581,423, filed on Nov. 3, 2017, and entitled “ContinuouslyMonitoring and Updating Mortgage Ready Data,” the entire disclosures ofwhich are expressly incorporated by reference herein for all purposes.

TECHNICAL FIELD

This disclosure relates to systems and methods for approving a mortgageapplication and, more particularly, at least in some embodiments, tosystems and methods for approving and updating a mortgage applicationusing computing and/or blockchain technologies.

BACKGROUND

During a conventional mortgage loan process, it may typically take atleast 30 days to meet all the requirements necessary for a real estateproperty to close, e.g., officially transfer the property from one ownerto another owner. More specifically, various items are needed to closethe property, each of which may include a certain period of time tocomplete. For example, a home buyer's mortgage application must beapproved, which may require the home buyer to submit various items ofinformation to a bank for review. In addition, a home appraisal may berequired, which may typically involve an inspector physically reviewingand evaluating the condition of the real estate property and preparing areport. Further, proof of a title search evidencing ownership of theproperty, for example, may be required along with proof of homeowner'sand mortgage insurance.

As is well known in the industry, all of these components of the processmay require some time and together often result in at least 30,sometimes 45 days, to enable the real estate property to be closed. Thistime delay has several drawbacks, including inconvenience, and oftenfrustration, for those involved.

SUMMARY

The present embodiments relate to closing on a property at a faster ratethan the typical time period of at least 30 days. Home buyers, e.g.,mortgagees, often desire a faster close once securing a contract to buya real estate property for various reasons. Such reasons include wantingto begin renovations on, or having to move into, the real estateproperty as soon as possible. Likewise, lenders, such as various banks,may also desire a faster closing process at least to generate and securethe revenue from the closing at a faster rate. In addition, fasterclosing processes may result in fewer problems during the time periodleading up to the closing, resulting in fewer failed real estatetransactions. Still further, like both home buyers and lenders,insurance companies may also be interested in a faster closing process.

In one aspect, the present embodiments may relate determining that acustomer, a property or home, and/or a local government entity is“mortgage ready.” For instance, a home may already have an appraisalperformed on it recently, a customer may have submitted recent financialinformation, and/or a government entity may be set up for handlinge-titles/electronic titles or otherwise be capable of handlingelectronic deeds. If the home buyer, home, and/or local governmententity is maintained in a mortgage ready condition, the processing timefor home closing may be streamlined.

In another aspect, a computer-implemented method of using a blockchainto determine a customer is approved for a mortgage may be provided. Themethod may include: (1) receiving, at one or more processors, a requestfor a mortgage associated with a customer identification number; (2)identifying, via the one or more processors, a blockchain associatedwith the customer, the customer's blockchain may be identified using thecustomer identification number; (3) accessing, at a memory coupled tothe one or more processors, the blockchain corresponding to the customeridentification number to retrieve information about the customer, theinformation including one or more of customer age, marital status,homeowner status, income level, occupation, finances or income,insurance status, education level, employment status, telematics data,credit score data, deposit account data for down payment, and currentpayment stub data; (4) verifying, via the one or more processors, noincreased risk event occurred, the increased risk event including one ormore of a decrease in the deposit account data for down payment, adeclaration of bankruptcy, a decrease in credit score, an unemploymentclaim, or old or expired pay stub data; and/or (5) calculating, via theone or more processors, an amount the customer is approved for amortgage loan based upon the retrieved information about the customerand indicating, via the one or more processors, the customer is mortgageready. The method may include additional, less, or alternative actions,including those discussed elsewhere herein.

In another aspect, a computer-implemented method of using blockchaintechnology to determine a real estate property is mortgage ready may beprovided. The method may include: (1) receiving, at one or moreprocessors, a request for an appraisal associated with one or more of areal estate property identification number (PIN) and/or a multiplelisting service (MLS) number; (2) identifying, via the one or moreprocessors, a blockchain associated with the real estate property, thereal estate property's blockchain may be identified using the PIN and/orMLS number; (3) accessing, at a memory coupled to the one or moreprocessors, the blockchain corresponding to the PIN and/or MLS number toretrieve information about the real estate property, the informationincluding one or more of list price, real estate property age,historical appraisal data, age of roof, age of siding, age of driveway,age of one or more appliances, basement remodel data, square footagedata, number of bathrooms, number of bedrooms, flood or water damagedata, neighborhood crime score, proximity to public transportation,proximity to airport, proximity to major metropolitan area, proximity torecreation, school district data, fire or flood claims in neighborhood,building materials data for new construction, and/or repairs data; (4)verifying, via the one or more processors, no increased risk eventoccurred, the increased risk event including one or more of anindication a claim for damages was filed or the property is in one ormore of a hurricane zone, a flood zone, or an earthquake zone; (5)calculating, via the one or more processors, an appraisal value for thereal estate property based upon the retrieved information about the realestate property from the blockchain; (6) comparing, via the one or moreprocessors, the calculated appraisal value with the list price accessedfrom the blockchain corresponding to the PIN and/or MLS number; and/or(7) indicating, via the one or more processors, the real estate propertyis mortgage ready when the calculated appraisal value is equal to, orexceeds, the list price value. The method may include additional, less,or alternate actions, including those discussed elsewhere herein.

In another aspect, a computer-implemented method of approving a dynamicmortgage application may be provided. The method may include: (1)determining, via one or more processors, a customer is approved for amortgage, including calculating, via the one or more processors, anamount in which the customer is approved for a mortgage loan based uponthe information about the customer retrieved from the blockchain; (2)determining, via one or more processors, a real estate property ismortgage ready, including calculating, via the one or more processors,an appraisal value for the real estate property based upon theinformation about the real property retrieved from the blockchain; (3)comparing, via the one or more processors, the calculated amount thecustomer is approved for a mortgage loan with the calculated appraisalvalue of the real estate property; and/or (4) approving the mortgageapplication of the customer for the real estate property when thecalculated amount the customer is approved for the mortgage loan meets,or exceeds, the calculated appraisal value of the real estate property,reducing a processing time and closing time of the mortgage. The methodmay include additional, less, or alternate actions, including thosediscussed elsewhere herein.

In yet another aspect, a computer-implemented method of using blockchaintechnology to continuously update information about a customer approvedfor a mortgage may be provided. The customer may be associated with acustomer identification number. The method may include: (1) monitoring,via one or more processors, information accessed from a blockchaincorresponding to the customer identification number, the informationused to determine the customer is approved for a mortgage and includingone or more of customer age, marital status, homeowner status, incomelevel, occupation, finances or income, insurance status, educationlevel, employment status, telematics data, credit score data, depositaccount data for down payment, and current payment stub data; (2)receiving, at the one or more processors, new information about thecustomer, the new information used to determine the customer is approvedfor a mortgage and including one or more of customer age, maritalstatus, homeowner status, income level, occupation, finances or income,insurance status, education level, employment status, telematics data,credit score data, deposit account data for down payment, and currentpayment stub data; (3) updating, at a memory coupled to the one or moreprocessors, a block of the blockchain to include the new information;and/or (4) recalculating, via the one or more processors, the amount inwhich the customer is approved for a mortgage based upon the newinformation received. The method may include additional, less, oralternate actions, including those discussed elsewhere herein.

In another aspect, a computer-implemented method of identifying multiplemortgage ready properties using a blockchain may be provided. Eachmortgage ready property is associated with a property identificationnumber (PIN) and/or a multiple listing service (MLS) number. The methodmay include: (1) receiving, at one or more processors, information froma customer approved for a mortgage about preferences for a real estateproperty, the information including customer preference for one or moreof real estate property list price, age, historical appraisal data, ageof roof, age of siding, age of driveway, age of appliances, basementremodel data, square footage data, number of bathrooms, number ofbedrooms, flood or water damage, neighborhood crime score, proximity topublic transportation, proximity to airport, proximity to majormetropolitan area, proximity to recreation, school district data, fireor flood claims in neighborhood, building materials for newconstruction, repairs data, and price range; (2) accessing, at a memorycoupled to the one or more processors, a blockchain to retrieve aplurality of mortgage ready real estate properties meeting one or moreof the customer preferences information; and/or (3) transmitting, viathe one or more processors, the plurality of real estate propertiesmeeting one or more of the customer preferences information to thecustomer. The method may include additional, less, or alternate actions,including those discussed elsewhere herein.

In still yet another aspect, a computer-implemented method ofincentivizing an insurance agent to update a blockchain may be provided.The method may include: (1) receiving, at one or more processors, amessage indicating an agent updated a blockchain with information abouta customer or a real estate property; (2) increasing, via the one ormore processors and according to an interval of time, a score of theagent for at least one item of information about one or more of thecustomer or the real estate property updated to the blockchain, theinterval of time including one or more of real time, daily, weekly,bi-weekly, monthly, or quarterly; and/or (3) calculating, via the one ormore processors, an agent rating based upon the score of the agent, theagent rating used to compute one or more of compensation or bonus of theagent. The method may include additional, less, or alternate actions,including those discussed elsewhere herein.

In still yet another aspect, a computer-implemented method ofdetermining a customer is approved for a mortgage may be provided. Themethod may include receiving, at one or more processors, a request for amortgage associated with a customer identification number, andidentifying, via the one or more processors, a memory storage locationassociated with the customer, the customer's memory storage location maybe identified using the customer identification number. The method mayalso include accessing, at a memory coupled to the one or moreprocessors, the memory storage location corresponding to the customeridentification number to retrieve information about the customerrelative to obtaining a mortgage. The method may further includeverifying, via the one or more processors, no increased risk eventoccurred, and calculating, via the one or more processors, an amount thecustomer is approved for a mortgage loan based upon the retrievedinformation about the customer and indicating, via the one or moreprocessors, the customer is mortgage ready, reducing the processing timefor a mortgage approval. The method may include additional, less, oralternate actions, including those discussed elsewhere herein.

In yet another aspect, a computer-implemented method of determining areal estate property is mortgage ready may be provided. The method mayinclude receiving, at one or more processors, a request for an appraisalassociated with one or more of a real estate property identificationnumber (PIN) and/or a multiple listing service (MLS) number, andidentifying, via the one or more processors, a memory storage locationassociated with the real estate property, the real estate property'scomputer file or memory location may be identified using the PIN and/orMLS number. The method may include accessing, at a memory coupled to theone or more processors, the memory storage location corresponding to thePIN and/or MLS number to retrieve information about the real estateproperty, and verifying, via the one or more processors, no increasedrisk event occurred. The method may further include calculating, via theone or more processors, an appraisal value for the real estate propertybased upon the retrieved information about the real estate property fromthe memory storage location, and comparing, via the one or moreprocessors, the calculated appraisal value with the list price accessedfrom the memory storage location corresponding to the PIN and/or MLSnumber. The method may also include indicating, via the one or moreprocessors, the real estate property is mortgage ready when thecalculated appraisal value is equal to, or exceeds, the list pricevalue. The method may include additional, less, or alternate actions,including those discussed elsewhere herein.

In still another aspect, a computer-implemented method of approving adynamic mortgage application may be provided. The method may includedetermining, via one or more processors, a customer is approved for amortgage, including calculating, via the one or more processors, anamount in which the customer is approved for a mortgage loan based uponthe information about the customer retrieved from a memory storagelocation. The method may include determining, via one or moreprocessors, a real estate property is mortgage ready, includingcalculating, via the one or more processors, an appraisal value for thereal estate property based upon the information about the real propertyretrieved from the memory storage location, such as by using a machinelearning or an artificial intelligence algorithm. The method may includecomparing, via the one or more processors, the calculated amount thecustomer is approved for a mortgage loan with the calculated appraisalvalue of the real estate property. The method may also include approvingthe mortgage application of the customer for the real estate propertywhen the calculated amount the customer is approved for the mortgageloan meets, or exceeds, the calculated appraisal value of the realestate property, reducing a processing time and closing time of themortgage. The method may include additional, less, or alternate actions,including those discussed elsewhere herein.

In yet another aspect, a computer system for approving a dynamicmortgage application of a customer for a real estate property may beprovided. The customer corresponds to a customer identification numberrecord tracked by a computer, such as a computer employing one or moremachine learning techniques, or via a memory storage location, and thereal estate property corresponds to a real estate propertyidentification number (PIN) record tracked by a computer, such as acomputer employing one or more machine learning techniques, or via amemory storage location. The system may include a network interfaceconfigured to interface with one or more processors, a memory configuredto store non-transitory computer executable instructions and configuredto interface with the one or more processors, and the one or moreprocessors configured to interface with the memory. In addition, the oneor more processors are configured to execute the non-transitory computerexecutable instructions to cause the system to: determine a customer isapproved for a mortgage loan based upon information about the customerretrieved from the memory storage location; determine a real estateproperty is mortgage ready based upon information about the real estateproperty retrieved from the memory storage location; compare acalculated amount the customer is approved for a mortgage loan with acalculated appraisal value of the real estate property; and/or approvethe mortgage application of the customer for the real estate propertywhen the calculated amount the customer is approved for the mortgageloan is equal to, or exceeds, the calculated appraisal value of the realestate property, reducing a processing time and closing time of themortgage. The system may include additional, less, or alternateelements, including those discussed elsewhere herein.

In still yet another aspect, a computer-implemented method ofcontinuously updating information about a customer approved for amortgage may be provided. The customer may be associated with a customeridentification number, and the method may include monitoring, via one ormore processors, information accessed from a memory storage locationcorresponding to the customer identification number, with theinformation being used to determine the customer is approved for amortgage. The method further may include receiving, at the one or moreprocessors, new information about the customer, the new information usedto determine the customer is approved for a mortgage. The method mayalso include updating, at a memory coupled to the one or moreprocessors, the memory storage address to include the new information;and recalculating, via the one or more processors, the amount in whichthe customer is approved for a mortgage based upon the new informationreceived. The method may include additional, less, or alternate actions,including those discussed elsewhere herein.

In yet another aspect, a computer-implemented method of continuouslyupdating information about a real estate property identified as mortgageready may be provided. The real estate property may be associated with areal estate property identification number (PIN) and/or a multiplelisting service (MLS) number. The method may include monitoring, via oneor more processors, information about the real estate propertycorresponding to the PIN and/or MLS number, the information used todetermine the real estate property is mortgage ready, and/oridentifying, via the one or more processors, new information about thereal estate property, the new information including any of theinformation used to determine the real estate property is mortgageready. The method may further include updating, at a memory coupled tothe one or more processors, a memory storage location to include the newinformation about the real estate property; and/or recalculating, viathe one or more processors, the appraisal value for the real estateproperty based upon the new information received. The method may includeadditional, less, or alternate actions, including those discussedelsewhere herein.

In still yet another aspect, a computer system for continuously updatinginformation about one or more of a customer approved for a mortgage anda real estate property identified as mortgage ready using computertechnology and/or machine learning algorithms or artificial intelligenceis disclosed. The customer may be associated with a customeridentification number record tracked by a memory storage location, andthe real estate property corresponds to a real estate propertyidentification number (PIN) record tracked by a memory storage location.The system may include a network interface configured to interface withone or more processors of an insurance entity, and a memory configuredto store non-transitory computer executable instructions and configuredto interface with the one or more processors. The one or more processorsmay be configured to interface with the memory and to execute thenon-transitory computer executable instructions to cause the system to:monitor information corresponding to one or more of the customer or thereal estate property; identify new information about one or more of thecustomer or the real estate property; update a memory storage locationto include the new information about one or more of the customer or thereal estate property; and/or recalculate one or more of the amount inwhich the customer is approved for the mortgage or the appraisal valueof the real estate property based upon one or more of new informationreceived and the updated information from the memory storage location.The system may include additional, less, or alternate elements,including those discussed elsewhere herein.

In still another aspect, a computer-implemented method of identifyingmultiple mortgage ready properties using computer technology and/ormachine learning algorithms or artificial intelligence is disclosed.Each mortgage ready property is associated with a propertyidentification number (PIN) and/or a multiple listing service (MLS)number. The method may include receiving, at one or more processors,information from a customer approved for a mortgage about preferencesfor a real estate property, and accessing, at a memory coupled to theone or more processors, a memory storage location to retrieve aplurality of mortgage ready real estate properties meeting one or moreof the customer preferences information. The method may includetransmitting, via the one or more processors (and/or associatedtransceivers), the plurality of real estate properties meeting one ormore of the customer preferences information to the customer. The methodmay include additional, less, or alternate actions, including thosediscussed elsewhere herein.

In still yet another aspect, a computer system for identifying multiplemortgage ready properties using computer technology and/or machinelearning technologies may be provided. Each mortgage ready property maybe associated with a property identification number (PIN) and/or amultiple listing service (MLS) number. The system may include a networkinterface configured to interface with one or more processors of anentity, and a memory configured to store non-transitory computerexecutable instructions and configured to interface with the one or moreprocessors. The one or more processors are configured to interface withthe memory. In addition, the one or more processors are configured toexecute the non-transitory computer executable instructions to cause thesystem to: receive information from a customer approved for a mortgageabout preferences for a real estate property; access a memory associatedwith a memory storage location to retrieve a plurality of real estateproperties meeting one or more of the customer preferences information,each real estate property of the plurality of real estate propertiesbeing mortgage ready; and/or transmit the identified plurality of realestate properties meeting the customer preferences information to thecustomer. The method may include additional, less, or alternate actions,including those discussed elsewhere herein.

In still yet another aspect, a computer-implemented method ofincentivizing an insurance agent to update a memory storage location maybe provided. The method may include receiving, at one or moreprocessors, a message indicating an agent updated a memory storagelocation with information about a customer or a real estate property.The method may also include increasing, via the one or more processorsand according to an interval of time, a score of the agent for at leastone item of information about one or more of the customer or the realestate property updated to the memory storage location. The interval oftime may include one or more of real time, daily, weekly, bi-weekly,monthly, or quarterly. The method may also include calculating, via theone or more processors, an agent rating based upon the score of theagent, the agent rating used to compute one or more of compensation orbonus of the agent. The method may include additional, less, oralternate actions, including those discussed elsewhere herein.

In yet another aspect, a computer system for incentivizing an insuranceagent to update a memory storage location may be provided. The systemmay include a network interface configured to interface with one or moreprocessors of an entity and a memory configured to store non-transitorycomputer executable instructions and configured to interface with theone or more processors. The one or more processors are configured tointerface with the memory and to execute the non-transitory computerexecutable instructions to cause the system to: receive one or more of amessage or a signal indicating an agent updated a memory storagelocation with information about one or more of a customer or a realestate property; increase a score of the agent for at least one item ofinformation about one or more of the customer or the real estateproperty updated to the memory storage location; and/or calculate anagent rating based upon the score of the agent. The system may includeadditional, less, or alternate elements, including those discussedelsewhere herein.

Advantages will become more apparent to those skilled in the art fromthe following description of the preferred embodiments which have beenshown and described by way of illustration. As will be realized, thepresent embodiments may be capable of other and different embodiments,and their details are capable of modification in various respects.Accordingly, the drawings and description are to be regarded asillustrative in nature and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

The Figures described below depict various aspects of the system andmethods disclosed therein. It should be understood that each figuredepicts an example of a particular aspect of the disclosed system andmethods, and that each of the figures is intended to accord with apossible example thereof. Further, wherever possible, the followingdescription refers to the reference numerals included in the followingfigures, in which features depicted in multiple figures are designatedwith consistent reference numerals.

There are shown in the drawings arrangements which are presentlydiscussed, it being understood, however, that the present examples arenot limited to the precise arrangements and instrumentalities shown,wherein:

FIG. 1A is an exemplary computing environment including componentsassociated with a system and method of approving a dynamic mortgageapplication using blockchain technology in accordance with one aspect ofthe present disclosure;

FIG. 1B is an exemplary computing environment including componentsassociated with a system and method of approving a dynamic mortgageapplication in accordance with another aspect of the present disclosure;

FIG. 2 depicts an exemplary computer system in which some of thetechniques described herein may be implemented in accordance with oneaspect of the present disclosure;

FIG. 3A depicts an exemplary distributed ledger system, such as ablockchain system, in accordance with one aspect of the presentdisclosure;

FIG. 3B depicts an exemplary sequence diagram of the distributed ledgersystem of FIG. 3A;

FIG. 4 depicts an exemplary node of the distributed ledger system ofFIG. 3 in accordance with an aspect of the present disclosure;

FIG. 5 depicts an exemplary blockchain in accordance with one aspect ofthe present disclosure;

FIG. 6 depicts an exemplary computer-implemented method of utilizingblockchain technology to determine a customer is approved for amortgage;

FIG. 7 depicts an exemplary computer-implemented method of utilizingblockchain technology to determine a real estate property is mortgageready;

FIG. 8 depicts an exemplary computer-implemented method of using ablockchain to approve a dynamic mortgage application;

FIG. 9 depicts an exemplary computer-implemented method of utilizingblockchain technology to continuously update information about acustomer approved for a mortgage;

FIG. 10 depicts an exemplary computer-implemented method of utilizingblockchain technology to continuously update information about a realestate property identified as mortgage ready;

FIG. 11 depicts an exemplary computer-implemented method of utilizingblockchain technology to identify multiple mortgage ready propertiesbased upon customer input;

FIG. 12 depicts an exemplary computer-implemented method ofincentivizing an agent to update a blockchain;

FIG. 13 is a front view of an exemplary computing device of the systemand method of approving a dynamic mortgage application of FIGS. 1A and1B;

FIG. 14 is another front view of the exemplary computing device of thesystem and method of approving a dynamic mortgage application of FIGS.1A and 1B, the exemplary computing device displaying a prompt forinformation relative to verifying an identity of the customer;

FIG. 15 is another front view of the exemplary computing device of thesystem and method of approving a dynamic mortgage application of FIGS.1A and 1B, the exemplary computing device displaying bank accountinformation relative to an identified customer;

FIG. 16 is another front view of the exemplary computing device of thesystem and method of approving a dynamic mortgage application of FIGS.1A and 1B, the exemplary computing device displaying a calculated amountthe identified customer is approved for a mortgage; and

FIG. 17 is another front view of the exemplary computing device of thesystem and method of approving a dynamic mortgage application of FIGS.1A and 1B, the exemplary computing device displaying a listing ofmortgage ready real estate properties.

The Figures depict preferred embodiments for purposes of illustrationonly. One skilled in the art will readily recognize from the followingdiscussion that alternative embodiments of the systems and methodsillustrated herein may be employed without departing from the principlesof the invention described herein.

DETAILED DESCRIPTION

Generally, the present disclosure and exemplary aspects relate to, interalia, systems and methods for utilizing blockchain technology to approvea dynamic mortgage application. For example, a blockchain may be used toapprove a customer for a mortgage amount, determine and identify a realestate property as mortgage ready (e.g., having a calculated appraisalvalue using information about the real estate property accessed from theblockchain that meets, or exceeds, a list price of the real estateproperty), approve a dynamic mortgage application, monitor and updatethe mortgage ready data relative to both the customer and the realestate property, and identify multiple mortgage ready properties basedupon customer input, and incentivize and rate insurance agents basedupon the customer and real estate property mortgage ready data receivedfrom the agent. In one example, the systems and methods described hereinallow for using a private blockchain of an insurance entity, which givesthe option for private information and permissioned participants in theblockchain.

The disclosed systems and methods may use an application of distributedledgers, where each new block may be cryptographically linked to theprevious block in order to form a “blockchain,” as described in moredetail below. More particularly, to create a new block, each transactionwithin a block may be assigned a hash value (i.e., an output of acryptographic hash function). These hash values may then be combinedutilizing data storage and cryptographic techniques (e.g., a MerkleTree) to generate a hash value representative of the entire new block,and, consequently, the transactions stored in the block. This hash valuemay then be combined with the hash value of the previous block to form ahash value included in the header of the new block, therebycryptographically linking the new block to the blockchain. To this end,the precise value utilized in the header of the new block is dependenton the hash value for each transaction in the new block, as well as thehash value for each transaction in every prior block.

Exemplary Environment for Approving a Dynamic Mortgage Application UsingBlockchain Technology

FIG. 1A depicts an exemplary computing environment 10 includingcomponents associated with approving a dynamic mortgage applicationusing blockchain technology in accordance with one aspect of the presentdisclosure. As illustrated in FIG. 1A, the environment 10 may include Ncomputing devices 12-1 through 12-N associated with N respectivecustomers (e.g., thousands of customers, millions of customers, etc.).Each of the computing devices 12-1 through 12-N may be any suitable typeof computing device having wired and/or wireless communicationcapabilities, such as a personal computer, tablet, phablet, smartphone,etc.

The environment 10 may also include a computing system 14 associatedwith an insurance entity. The computing system 14 may include one ormore servers of the insurance entity, or may include a plurality ofnetworked computing devices that have an appearance of a single, logicalcomputing device or system, e.g., a group of cloud computing devices.The computing system 14 may be communicatively coupled to computingdevices 12-1 through 12-N via a network (not shown in FIG. 1A). Thenetwork may be a single communication network, or may include multiplecommunication networks of one or more types (e.g., one or more wiredand/or wireless local area networks (LANs), and/or one or more wiredand/or wireless wide area networks (WANs) such as the Internet), forexample.

The environment 10 may also include a computing system 16 associatedwith a realtor entity, a computing system 18 associated with a bankentity, and a computing system 20 associated with a county entity. Eachof the computing systems 16, 18 and 20 may include one or more serversor computing devices and may be communicatively coupled to computingsystem 14 of the insurance entity via a network (not shown in FIG. 1A).The network may be a single communication network, or may includemultiple communication networks of one or more types (e.g., one or morewired and/or wireless LANs, and/or one or more wired and/or wirelessWANs such as the Internet), for example.

The computing system 14 may include various units, including a customerunit 22, a real estate property unit 24, and an insurance agent unit 26.Each of some or all of the units 22, 24 and 26 may include a respectiveset of one or more computing devices or processors that execute softwareinstructions to perform the corresponding functions described herein.Alternatively, each of some or all of the units 22, 24 and 26 may be orinclude a respective component of software that is stored on one or morecomputer-readable media (e.g., a random access memory (RAM) and/orread-only memory (ROM) of the computing system 14) and executed by oneor more processors of the computing system 14 to perform thecorresponding functions described herein. Further, one or more of theunits may be combined into a single unit, or may be omitted. Inaddition, the computing system 14 of the insurance entity may furtherinclude a blockchain system 200, which is explained more below and inFIG. 3A, for example. The blockchain system 200 may be a part of one ormore of the units 22, 24, 26 or only one of the units when the units arecombined into a single unit, for example.

Generally, in one embodiment, customer unit 22 collects informationregarding the customers operating computing devices 12-1 through 12-N(with customer permission, affirmative consent, or via the customer),stores the collected information in a customer profile database thatincludes a separate profile for each customer, and updates theblockchain system 200 with the customer information, creating a digitalidentity for each customer on the blockchain system 200, for example.The customer profile database may be any suitable type of persistentmemory. The customer unit 22 may obtain the customer information in anyof one or more ways. For example, customer unit 22 may obtaindemographic information (e.g., gender, birth date) and information aboutcustomer's finances and employment via on-line forms (e.g., insuranceapplications, mortgage applications) filled out by the customers usingcomputing devices 12-1 through 12-N. The customer unit 22 may providethe on-line forms as one or more web pages (e.g., HTML files, JavaServerPages files, etc.) stored in a memory of the computing system 14, andthe consumers may use web browser applications executing on thecomputing devices 12-1 through 12-N to access the web page(s), forexample.

Via the on-line forms, or via other suitable means, customer unit 22 mayalso collect insurance preferences and/or requirements of the variouscustomers. For example, each customer may enter his or her preferred orrequired coverage types, coverage limits, deductibles, insuranceprovider ratings (e.g., AAA), and/or any other preference or requirementrelating to insurance. A customer may indicate that he or she prefers tohave a policy through an insurance company that offers live insuranceagents, for example. In an alternative embodiment and/or scenario, someor all of the consumers provide information via physical applicationforms, and some or all of the computing devices 12-1 through 12-N may beomitted in the example environment 10. Generally, the customer unit 22may store the individual preferences of a particular customer (orindications thereof) in a respective customer profile of the customerprofile database of the customer unit 22, for example.

Further, the customer unit 22 may collect other information that is alsoto be stored in the customer database (with customer permission). For acustomer already having an insurance policy with the insurance entity14, such as an insurance provider, for example, customer unit 22 mayreceive or obtain information from the customer's insurance accountand/or policy. For example, claims information from that provider (e.g.,number and/or dates of past claims, past claim payouts made to or onbehalf of the consumer, etc.) may be obtained. Alternatively, oradditionally, customer unit 22 may receive telematics data relative tothe customer's existing real estate property and health or lifestylehabits. Generally, the customer unit 22 may store individualcharacteristics of a particular customer (or indications thereof) in arespective customer profile within the customer profile database.Individual customer characteristics or customer information may include,for example, customer age, marital status, homeowner status,geographical location, income level, occupation, finances or income,insurance status, education level, employment status, telematics data,credit score data, deposit account data for down payment, and currentpayment stub data. Customer unit 22 may then update the blockchainsystem 200 of the insurance entity 14 to include all of the customerinformation about each of the customers, creating the digital identityfor each customer on the blockchain system 200, for example.

With the foregoing, a customer may opt-in to a rewards, insurancediscount, or other type of program. After the customer provides theiraffirmative consent, an insurance provider remote server may collectdata from the customer's mobile device, smart home controller, smart orautonomous vehicle, or other smart devices—such as with the customer'spermission or affirmative consent. The data collected may be related tosmart home functionality (or home occupant preferences or preferenceprofiles), smart or autonomous vehicle functionality, and/or insuredassets before (and/or after) an insurance-related event, including thoseevents discussed elsewhere herein. In return, risk averse insureds, homeowners, or home or apartment occupants may receive discounts orinsurance cost savings related to home, renters, personal articles,auto, and other types of insurance from the insurance provider, and suchinformation may be further collected by the insurance entity 14, such asby the customer unit 22.

In one aspect, smart or interconnected home data, and/or other data,including the types of data discussed elsewhere herein, may be collectedor received by an insurance provider remote server, such as via director indirect wireless communication or data transmission from a smarthome controller, mobile device, smart or autonomous vehicle, or othercustomer computing device, after a customer affirmatively consents orotherwise opts-in to an insurance discount, reward, or other program.The insurance entity 14, such as the insurance provider, may thenanalyze the data received with the customer's permission to providebenefits to the customer. As a result, risk averse customers may receiveinsurance discounts or other insurance cost savings based upon data thatreflects low risk behavior and/or technology that mitigates or preventsrisk to (i) insured assets, such as homes, personal belongings, orvehicles, and/or (ii) home or apartment occupants. Such information maybe further collected by the insurance entity 14, such as by the customerunit 22.

In a similar manner, the real estate property unit 24 may collectinformation regarding various real estate properties the insuranceentity 14 is currently insuring. Alternatively, or additionally, thereal estate property unit 24 may collect real estate propertyinformation transmitted to the insurance entity 14 by one or more of thecomputing system 16 associated with the realtor entity, the computingsystem 18 associated with the bank entity, or the computing system 20associated with the county entity. The real estate property unit 24 maythen store the collected information about each real estate property ina database of the real estate property unit 24, for example, thatincludes a separate profile for each real estate property. The databasemay again be any suitable type of persistent memory. In addition, thereal estate property unit 24 may then update the blockchain system 200with the real estate property information collected, creating a digitalidentity for each real estate property on the blockchain system 200, inone example.

The real estate property unit 24 may obtain the real estate propertyinformation in any of one or more ways. For example, real estateproperty unit 24 may obtain information about the real estate propertyvia on-line forms (e.g., appraisal and mortgage applications) filled outby individuals operating the computing system 16 of the realtor entityand/or the computing system 18 of the bank entity, e.g., the bank entityproviding the mortgage associated with the real estate property.Alternatively, and/or additionally, the real estate property unit 24 mayobtain the real estate property information by accessing a blockchain 21of the computing system 20 of the county entity, as explained morebelow. Still further, the real estate property unit 24 may obtain thereal estate property information from the insurance agent unit 26associated with the insurance entity. In that example, the insuranceagent providing the homeowner's and/or mortgage insurance for the realestate property may provide information to the real estate property unit24 about the real estate property. Such real estate property informationmay include one or more of the real estate property age, historicalappraisal data, age of roof, age of siding, age of driveway, age of oneor more appliances, basement remodel data, square footage data, numberof bathrooms and/or bedrooms, flood or water damage data, neighborhoodcrime score, proximity to public transportation, proximity to airport,proximity to major metropolitan area, proximity to recreation, schooldistrict data, fire or flood claims in neighborhood, building materialsdata for new construction, repairs data and/or any other real estateproperty characteristics.

Further, the real estate property unit 24 may collect other informationthat is also to be stored in a database and updated to the blockchainsystem 200 of the insurance entity 14, for example. In one example, fora real estate property already having an insurance policy with theinsurance entity 14, such as an insurance provider, for example, thereal estate property unit 24 may receive or obtain information from thereal estate property's insurance account and/or policy. For example,claims information from that provider (e.g., number and/or dates of pastclaims, past claim payouts made relative to the real estate property)may be obtained. Alternatively, or additionally, real estate propertyunit 24 may receive telematics data relative to the customer's existingreal estate property and health or lifestyle habits. Generally, the realestate property unit 24 may then store individual characteristics of aparticular real estate property (or indications thereof) and update theblockchain to include the information about the real estate property.

Referring now to FIG. 1B, another exemplary computing environmentincluding components associated with a system and method of approving adynamic mortgage application in accordance with another aspect of thepresent disclosure is depicted. This exemplary environment is identicalto the exemplary computing environment of FIG. 1A, except the insuranceentity 14 does not include the blockchain system 200 as depicted in FIG.1A, but rather a more general memory storage location 27, as explainedmore below. As such, parts of the exemplary environment of FIG. 1B thatare the same as parts of the exemplary environment of FIG. 1A have thesame reference numbers and no further explanation is provided herein forthe sake of brevity. Different parts, namely the memory storage location27, however, have different reference numbers and are explained morebelow and throughout the description.

In particular, and in one example, the memory storage location 27 of theinsurance entity 14 may include one or more of a computer file, amemory, a memory location, or an address that may be associated with oneor more of the customer or the real estate property or properties. Inanother example, the memory storage location 27 may include one or moreof a blockchain system 200, a computer file, a memory, a memorylocation, or an address separate from the blockchain system 200, forexample. In yet another example, each of the computing systems 16, 18,20 of the realtor entity, bank entity, and county entity, respectively,may include one or more of a blockchain system or a memory storagelocation for example, as is explained more in the context of theexemplary computer system of FIG. 2.

Still further, an additional computing system 23 of a third party entity21 may also be included in the exemplary computing environment of FIG.1B. Like the computing systems 16, 18, 20, the computing system 23 ofthe third party entity may include one or more of a separate memorystorage location and/or a blockchain system separate from one or more ofthe blockchain systems of one or more of the computing systems 14, 16,18, 20 corresponding, respectively, to the insurance entity, realtorentity, bank entity or county entity.

In addition, the computing system 23 of the third party entity mayinclude one or more of Equifax, Instatouch, Maxwell, FinLocker, or anyother third party able to provide information needed for determining orcalculating whether the customer or real estate property is mortgageready, as further defined herein. Such information may include anyinformation relative to a digital identify of one or more of thecustomer or the real estate property, as further explained below.

Exemplary Computer System for Approving a Dynamic Mortgage ApplicationUtilizing Blockchain Technology

FIG. 2 depicts an exemplary computer system 100 in which the techniquesand methods described herein may be implemented, according to oneembodiment. In one embodiment, the computer system 100 may be includedin the system 10 of one or both of FIGS. 1A and 1B. For example, any oneor more of the units 22-26 may comprise one or more instances of thecomputer system 100, or the insurance entity 14 may comprise one or moreinstances of the computer system 100. In addition, any one or more ofthe computing systems 16, 18, 20, 21 of the realtor entity, the bankentity, the county entity, and the third party entity, respectively, maycomprise one or more instances of the computer system 100. Further, anyone or more of the computing devices of customers 12-1 through 12-N maycomprise one or more instances of the computer system 100.

The computer system 100 of FIG. 2 includes a computing device in theform of a computer 110. Components of the computer 110 may include, butare not limited to, a processing unit 120, a system memory 130, and asystem bus 121 that couples various system components including thesystem memory 130 to the processing unit 120. The system bus 121 may beany of several types of bus structures including a memory bus or memorycontroller, a peripheral bus, or a local bus, and may use any suitablebus architecture. In one example, the system memory 130 is the memorystorage location of each computing device 12.

Computer 110 typically includes a variety of computer-readable media.Computer-readable media can be any available media that can be accessedby computer 110 and may include both volatile and nonvolatile media, andboth removable and non-removable media. By way of example, and notlimitation, computer-readable media may comprise computer storage mediaand communication media. Computer storage media includes tangible,volatile and nonvolatile, removable and non-removable media implementedin any method or technology for non-transitory storage of informationsuch as computer-readable instructions, data structures, program modulesor other data. Computer storage media includes, but is not limited to,RAM, ROM, EEPROM, FLASH memory or other memory technology, CD-ROM,digital versatile disks (DVD) or other optical disk storage, magneticcassettes, magnetic tape, magnetic disk storage or other magneticstorage devices, or any other medium which can be used to store thedesired information and which can accessed by computer 110. Moregenerally and in one example, one or more of the aforementioned listingof computer storage media may be the memory storage location as definedherein. Communication media typically embodies computer-readableinstructions, data structures, program modules or other data in amodulated data signal such as a carrier wave or other transportmechanism, and includes any information delivery media. By way ofexample, and not limitation, communication media may include wired mediasuch as a wired network or direct-wired connection, and wireless mediasuch as acoustic, radio frequency (RF), infrared and other wirelessmedia. Combinations of any of the above are also included within thescope of computer-readable media.

The system memory 130, which may include the memory storage location inone example, may include computer storage media in the form of volatileand/or nonvolatile memory such as read only memory (ROM) 131 and randomaccess memory (RAM) 132. A basic input/output system 133 (BIOS),containing the basic routines that help to transfer information betweenelements within computer 110, such as during start-up, is typicallystored in ROM 131. RAM 132 typically contains data and/or programmodules that are immediately accessible to, and/or presently beingoperated on, by processing unit 120. By way of example, and notlimitation, FIG. 2 illustrates operating system 134, applicationprograms 135, other program modules 136, and program data 137.

The computer 110 may also include other removable/non-removable,volatile/nonvolatile computer storage media. By way of example only,FIG. 2 illustrates a hard disk drive 141 that reads from or writes tonon-removable, nonvolatile magnetic media, a magnetic disk drive 151that reads from or writes to a removable, nonvolatile magnetic disk 152,and an optical disk drive 155 that reads from or writes to a removable,nonvolatile optical disk 156 such as a CD ROM or other optical media.Other removable/non-removable, volatile/nonvolatile computer storagemedia that can be used in the exemplary operating environment include,but are not limited to, magnetic tape cassettes, flash memory cards,digital versatile disks, digital video tape, solid state RAM, solidstate ROM, and the like. The hard disk drive 141 may be connected to thesystem bus 121 through a non-removable memory interface such asinterface 140, and magnetic disk drive 151 and optical disk drive 155may be connected to the system bus 121 by a removable memory interface,such as interface 150.

The drives and their associated computer storage media discussed aboveand illustrated in FIG. 2 provide storage of computer-readableinstructions, data structures, program modules and other data for thecomputer 110. In FIG. 2, for example, hard disk drive 141 is illustratedas storing operating system 144, application programs 145, other programmodules 146, and program data 147. Note that these components may eitherbe the same as or different from operating system 134, applicationprograms 135, other program modules 136, and program data 137. Operatingsystem 144, application programs 145, other program modules 146, andprogram data 147 are given different numbers here to illustrate that, ata minimum, they are different copies. A user may enter commands andinformation into the computer 110 through input devices such as cursorcontrol device 161 (e.g., a mouse, touch pad, etc.) and keyboard 162. Amonitor 191 or other type of display device is also connected to thesystem bus 121 via an interface, such as a video interface 190. Inaddition to the monitor, computers may also include other peripheraloutput devices such as printer 196, which may be connected through anoutput peripheral interface 195.

The computer 110 may operate in a networked environment using logicalconnections to one or more remote computers, such as a remote computer180. The remote computer 180 may be a personal computer, a server, arouter, a network PC, a peer device or other common network node, andtypically includes many or all of the elements described above relativeto the computer 110, although only a memory storage device 181 has beenillustrated in FIG. 2. The logical connections depicted in FIG. 2include a local area network (LAN) 171 and a wide area network (WAN)173, but may also include other networks. Such networking environmentsare commonplace in hospitals, offices, enterprise-wide computernetworks, intranets and the Internet.

When used in a LAN networking environment, the computer 110 is connectedto the LAN 171 through a network interface or adapter 170. When used ina WAN networking environment, the computer 110 may typically include amodem 172 or other means for establishing communications over the WAN173, such as the Internet. The modem 172, which may be internal orexternal, may be connected to the system bus 121 via the input interface160, or other appropriate mechanism. The communications connections 170,172, which allow the device to communicate with other devices, are anexample of communication media, as discussed above. In a networkedenvironment, program modules depicted relative to the computer 110, orportions thereof, may be stored in the remote memory storage device 181.By way of example, and not limitation, FIG. 2 illustrates remoteapplication programs 185 as residing on memory device 181.

In some configurations, the computer 110 may be included in a pluralityof networked computers or computing devices that have the logicalappearance as a single, integral computing node, e.g., a cloud computingsystem. For example, the application programs 145, other program modules146 and/or program data 137 may be stored in and executed by thelogical, single computing node.

The techniques and methods for approving and updating a dynamic mortgageapplication using blockchain technology described herein may beimplemented in part within a computer system such as the computer system100 illustrated in FIG. 2. The computer 110 may be a server or computingdevice of the insurance entity 14 (e.g., within the computing system 14of FIG. 1), and the remote computer 180 may be a server or computingdevice of one or more of the computing systems 16, 18 and 20 of FIG. 1,for example. In some such embodiments, the LAN 171 may be omitted (e.g.,communications may between computer 110 and computer 3180 may only occurvia WAN 173). Application programs 135 and 145 may include programs thatimplement customer unit 22, the real estate property unit 24, and theinsurance agent unit 26 of FIG. 1, for example. Databases in each of theunits 22-26 may be stored on hard disk drive 141, magnetic disk 152 oroptical disk 156, for example.

In general, any of the storage media described above including but notlimited to the system memory 130, the ROM 131, the RAM 132, the harddisk drive 141, the magnetic disk 152 or the optical disk 156 maycomprise the memory storage location as defined herein.

Exemplary Distributed Ledger

Referring now to FIG. 3A, an exemplary distributed ledger system 200,such as a blockchain system, in accordance with one aspect of thepresent disclosure is depicted. An example of a distributed ledgersystem 200 is the blockchain system 200 of FIG. 1 described above. FIG.3A includes a plurality of nodes 212, 214, and 216, network connections218, and a distributed ledger 220 having a blockchain 222. In adistributed ledger system 200, each node maintains a copy of thedistributed ledger 220, which includes a copy of the blockchain 222. Aschanges are made to the distributed ledger 200, each node updates theirrespective copy of the distributed ledger 220. A consensus mechanism maybe used by the nodes in the distributed ledger system 200 to decidewhether it is appropriate to make changes to the distributed ledger 220,as explained more below.

Therefore, each node has their own copy of the distributed ledger 220,which is identical to every other copy of the distributed ledger 220stored by each other node. The distributed ledger system 220 is morerobust than a central authority database system, for example, becausethe distributed ledger system 220 is decentralized. As such, there is nosingle point of failure.

Exemplary Sequence Diagram

FIG. 3B depicts an exemplary sequence diagram 300 in accordance with oneaspect of the blockchain system 200 of the present disclosure. FIG. 3Bincludes a set of nodes 212, 214 and 216. At 302, Node A 212 maygenerate a transaction. The transaction may be transmitted from Node A212 to Node C 216 at 304. Node C 216 may validate the transaction at306, and, if the transaction is valid, transmit the transaction at 308to Node B 214. Node B 214 may validate the transaction at 310. At 312,Node C 216 may compile a block including the validated transaction.Compiling a block may include generating a solution to a cryptographicpuzzle, and linking the block to other blocks, as described above. Oncethe block is compiled, Node C 216 may transmit the block with thesolution at 314 to both Node A 212 and Node B 214.

Both Node A 212 and Node B 214 may then validate the solution to theblock at 316. Verifying may include checking a cryptographic key-pair asdescribed above. At 318 the three nodes form a consensus that thesolution is valid, thereby forming a consensus on the blocks oftransactions stored by all the nodes.

Exemplary Node

FIG. 4 depicts an exemplary node 400 in accordance with one aspect ofthe present disclosure. In some embodiments, node 400 may be the sametype of node as Node C 216 in FIG. 3B. In other embodiments, node 400may be the same type of node as Node A 212 and Node B 214 in FIG. 3B.Node 400 may be capable of performing the functionality disclosedherein. In particular, node 400 may be utilized in the decentralizedsystem described in FIG. 3A, and/or the blockchain system 500 describedbelow in FIG. 5.

The node 400 may include at least one processor 402, memory 404, acommunication module 406, a set of applications 408, external ports 410,user interface 412, a blockchain manager 414, smart contracts 416,operating system 418, a display screen 420, and input/output components422. In some embodiments, the node 400 may generate a new block oftransactions of the blockchain by using the blockchain manager 414.Similarly, the node 400 may use the blockchain manager 414 inconjunction with the smart contracts 416 stored in memory 404 to executethe functionality disclosed herein.

In other embodiments, the smart contracts 416 operate independent of theblockchain manager 414 or other applications. In some embodiments, node400 does not have a blockchain manager 414, or smart contracts 416stored at the node. In some embodiments, the node 400 may haveadditional or less components than what is described. The components ofthe node 400 are described in more detail below.

The node 400, as part of a decentralized ledger system 200, or anotherdecentralized or centralized network, may be used as part of systemsthat interact with and/or manipulate data and transactions associatedwith the approving a dynamic mortgage application, including determininga customer is approved for a mortgage and determining real estateproperty is mortgage ready, as described more below.

Exemplary Blockchain System

FIG. 5 depicts an exemplary blockchain system 500 in accordance with oneaspect of the present disclosure. FIG. 5 includes a blockchain 502having at least one block of transactions 504. The blockchain 502 may bethe blockchain system 200 described above and depicted in FIG. 3A, forexample, or the blockchain of FIG. 4. The blockchain 502 furtherincludes a Merkle Tree 506 and a transaction 508. The Merkle Tree may bethe above-referenced Merkle Tree that cryptographically linkstransactions together. In other examples, the blockchain system 500 mayutilize a different method of organizing transactions in a block. Insome examples, the blockchain system 500 includes a plurality of blocksconnected together to form a chain of blocks of transactions 502.

Each block of transactions 504 may include at least one transaction 508.In other embodiments, each block of transactions 504 has a size limitthat necessarily limits the number of transactions that the block maystore. Each block of transactions 504 includes a reference to a previousblock of transactions that was added to the blockchain 502 prior to theblock of transactions 504 being added to the blockchain 502. As such,and as described above, each block of transactions 504 is linked toevery other block in the blockchain 502.

In some embodiments, the block of transactions 504 may organize thetransactions it has received into a Merkle Tree 506 to facilitate accessto the stored transactions. The transactions may be hashed using acryptographic hash algorithm, and the hash of each transaction may bestored in the tree. As the tree is constructed the hash of each adjacentnode at the same level may be hashed together to create a new node thatexists at a higher level in the tree. Therefore, the root of the tree,or the node at the top of the tree, is dependent upon the hash of eachtransaction stored below in the tree. Each transaction 508 may include aset of data 510. The set of data 510 may include identifying data forthe transaction, and transaction data identifying the nature of thetransaction and what the transactions entails

Exemplary Methods of Using a Blockchain to Approve a Dynamic MortgageApplication

FIG. 6 depicts an exemplary computer-implemented method 600 for using ablockchain to determine a customer is approved for a mortgage associatedwith one aspect of the present disclosure. The customer may be one ormore customers 12-1 through 12-N, as depicted in FIG. 1. Each customermay correspond to a respective customer identification number or recordtracked by a blockchain that is maintained by one or more participants.In some examples, the one or more participants may be one or more of thenodes 212, 214, 216 described above and depicted in FIG. 3A, forexample. In addition, the blockchain may be the blockchain 222 of theblockchain system 200 of FIG. 1 and/or the blockchain 500 of FIG. 5. Thesteps of the flow diagram may be performed by the nodes, such as thenodes depicted in FIG. 3A. The method 600 may include additional, fewer,or alternative actions, including those described elsewhere herein.

More specifically, and in one example, the method 600 may includereceiving, at one or more processors, such as the one or more processorsof the insurance entity 14, a request for a mortgage associated with acustomer identification number (block 602). Said another way, the one ormore processors may receive a request from a customer for a mortgage,and the customer may be associated with a customer identificationnumber. The method may further include identifying, via the one or moreprocessors of the insurance entity, one or more of a blockchain or amemory storage location associated with the customer. The customer'sblockchain or the customer's mortgage storage location may be identifiedusing the customer identification number (block 604), for example.

The method further may include accessing, at a memory coupled to the oneor more processors, one or more of the blockchain or the memory storagelocation corresponding to the customer identification number to retrieveinformation about the customer (block 606). The information about thecustomer may include one or more of customer age, marital status,homeowner status, income level, occupation, finances or income,insurance status, education level, employment status, telematics data,credit score data, deposit account data for down payment, and currentpayment stub data. According to some aspects, accessing one or more ofthe blockchain or the memory storage location may include verifying, atthe one or more processors, a notification source for the request forthe mortgagee; identifying, at the one or more processors, one or moreentries in one or more of the blockchain or memory storage locationcorresponding to the customer identification number or record for thecustomer; and accessing, at the memory, the one or more entries in oneor more of the blockchain or memory storage location corresponding tothe customer identification number records for the customer. Accordingto still other aspects, the blockchain system 200 may include one ormore of the blockchain system of the insurance entity 14 or theblockchain 500 depicted in FIG. 5.

The method may further include verifying, at the one or more processors,no increased risk event occurred (block 608). The increased risk eventmay include one or more of a decrease in the deposit account data fordown payment, a declaration of bankruptcy, a decrease in credit score,an unemployment claim, or old or dated pay stub data. In some examples,old or dated pay stub data may include a pay stub more than two weeksold or more than one month old.

The method then may also include calculating, at the one or moreprocessors, an amount the customer is approved for a mortgage loan basedupon the retrieved information about the customer (block 610). In oneexample, the one or more processors calculate the amount using one ormore of an algorithm or a set of rules based upon at least one or moreof the information about the customer listed above. In addition, themethod further may include indicating, at the one or more processors,the customer is mortgage ready (block 612), which reduces the processingtime for approving a mortgage application of the customer, as explainedmore below. Further, the method may further include updating, at thememory, one or more of a block for the blockchain or the memory storagelocation to indicate the customer is mortgage ready (block 614). Stillfurther, in yet still other aspects, the method may further includetransmitting, via the one or more processors coupled with the networkinterface, the block to another participant in the blockchain.

In some aspects, the method 600 may further include monitoring, via theone or more processors, the retrieved information about the customerfrom one or more of the blockchain or the memory storage location inreal time, such as via machine learning (such as supervised orunsupervised machine learning) or artificial intelligence algorithms.For example, machine learning may be utilized to identify increased riskevents across a pool of mortgage customers. Accordingly, the one or moreprocessors may monitor a plurality of mortgage transactions recorded inthe blockchain or the memory storage location to develop and/or trainthe machine learning algorithms associated with customer mortgage risk.To this end, upon the completion of the mortgage, the machine learningalgorithms may be adjusted based on the mortgage outcomes and/or theretrieved information about the customer. That is, if a mortgagesuccessfully is completed without any delays, the machine learningalgorithms that detect increased risk events may decrease weightsassociated with characteristics of the customer.

In one embodiment, machine learning techniques may also be used todetermine whether information associated with the consumer indicatesthat the consumer is mortgage ready. To this end, the machine learningalgorithms may develop and update weights for different types ofcustomer information, such as customer age, marital status, homeownerstatus, income level, occupation, finances or income, insurance status,education level, employment status, telematics data, credit score data,deposit account data for down payment, and current payment stub data.Based upon an analysis of the various weights, the machine learningalgorithms may determine that the customer is mortgage ready.

In another embodiment, machine learning techniques may also be used topredict the likelihood of a delay in the mortgage process and/or othernegative outcomes. For instance, rather than detecting whether anincreased risk event has occurred, the machine learning techniques mayanalyze the retrieved customer information to determine an overallcustomer risk profile. In some scenarios, the overall risk may bedetermined based on a plurality of sub-models that analyze individualaspects of mortgage risk. In this embodiment, an “increased risk event”may be the machine learning algorithm that assesses an overall customerrisk profile determining that the risk for the current customer exceedsa threshold value.

The method may still further include updating, via the one or moreprocessors and according to an interval of time, the amount in which thecustomer is approved for a mortgage loan based upon any changes in theinformation about the customer being monitored. The interval of time mayinclude one or more of real time, daily, every two weeks, monthly, everysix months and yearly.

Alternatively, and/or additionally, the method may further includereceiving, via the one or more processors, updated information about thecustomer. The updated information may include one or more of customerage, marital status, homeowner status, income level, occupation,finances or income, insurance status, education level, employmentstatus, telematics data, credit score data, deposit account data fordown payment, and current payment stub data. In this example, the methodmay then further include updating, at the memory, one or more of a blockfor the blockchain or the memory storage location to include and/orindicate the updated information about the customer received againaccording to an interval of time. The interval of time may include oneor more of real time, daily, bi-weekly, bi-monthly, monthly, bi-annuallyor annually. The updated blocks may then be transmitted, via one or moreof the processors, to other nodes in a communication network, forexample.

Referring now to FIG. 7, an exemplary computer-implemented method 700for using one or more of a blockchain or a memory storage location todetermine a real estate property is mortgage ready is depicted. Eachreal estate property may correspond to one or more of a respective realestate property identification number (PIN) (such as a taxidentification number), a multiple listing service (MLS) number orrecord, or street address or other record or identifier tracked by ablockchain that is maintained by one or more participants. In someexamples, the one or more participants may be one or more of the nodes212, 214, 216 described above and depicted in FIG. 3A, for example. Inaddition, the blockchain may be the blockchain 222 of the blockchainsystem 200 of FIG. 1 and/or the blockchain 500 of FIG. 5. The steps ofthe flow diagram may be performed by the nodes, such as the nodesdepicted in FIG. 3A. The method 700 may include additional, fewer, oralternative actions, including those described elsewhere herein.

As depicted in FIG. 7, the method may include receiving, at one or moreprocessors, a request for an appraisal associated with one or more of areal estate property identification number (PIN) and/or a multiplelisting service (MLS) number (block 702). In addition, the method mayinclude identifying, via the one or more processors, one or more of ablockchain or a memory storage location associated with the real estateproperty (block 704). In one example, the real estate property'sblockchain or memory storage location may be identified using the PINand/or MLS number. Further, the method may include accessing, at amemory coupled to the one or more processors, one or more of theblockchain or the memory storage location corresponding to the PINand/or MLS number to retrieve information about the real estate property(block 706). In some examples, the information includes one or more oflist price, real estate property list price age, historical appraisaldata, age of roof, age of siding, age of driveway, age of one or moreappliances, basement remodel data, square footage data, number ofbathrooms, number of bedrooms, flood or water damage data, neighborhoodcrime score, proximity to public transportation, proximity to airport,proximity to major metropolitan area, proximity to recreation, schooldistrict data, fire or flood claims in neighborhood, building materialsdata for new construction, street address or other location data, andrepairs data.

In addition, the method may include verifying, via the one or moreprocessors, no increased risk event occurred (block 708) or an increasedrisk event did not occur. The increased risk event may include one ormore of an indication a claim for damages was filed or the property isin one or more of a hurricane zone, a flood zone, or an earthquake zone.The method may further include calculating, via the one or moreprocessors, an appraisal value for the real estate property based uponthe retrieved information about the real estate property from theblockchain (block 710). In one example, the one or more processorscalculate the amount using an algorithm or one or more sets of rulesbased upon the real estate property information described above.

Still further, the method may include comparing, via the one or moreprocessors, the calculated appraisal value with the list price accessedfrom one or more of the blockchain or the memory storage locationcorresponding to the PIN and/or MLS number (block 712). Morespecifically, the one or more processors determine if the calculatedappraisal value is equal to, or exceeds, the list price (accessed fromthe blockchain, for example) (block 714). If yes, the one or moreprocessors further indicate that the real estate property is mortgageready (block 716). In some aspects, the method may further includeupdating, at the memory, one or more of a block for the blockchain orthe memory storage location to indicate the real estate property ismortgage ready (block 718). However, if the one or more processorsdetermine the calculated appraisal value does not equal, or exceed, thelist price, then the one or more processors may indicate the real estateproperty is not mortgage ready (block 720). In some aspects, the one ormore processors may then further update, at the memory, the block or thememory storage location to indicate the real estate property is notmortgage ready (block 722).

Similar to the method for using one or more of a blockchain or a memorystorage location to determine a customer is approved for a mortgageassociated described above, in some aspects the method 700 may furtherinclude monitoring, via the one or more processors, the retrievedinformation about the real estate property from one or more of theblockchain or the memory storage location in real time, such as viamachine learning or artificial intelligence algorithms. According tocertain aspects, the machine learning algorithms associated with themethod 700 may be implemented in a similar manner as described withrespect to the method 600 above. To this end, machine learningtechniques may be utilized to identify increased risk events based oncharacteristics of properties across a pool of properties and/or developan overall property risk profile.

In one embodiment, machine learning techniques, including supervised orunsupervised machine learning, may also be used to determine whetherinformation associated with the real estate property indicates that thereal estate property is mortgage ready. To this end, the machinelearning algorithm may develop and update weights for different types ofreal estate property information, such as real estate property listprice, age, historical appraisal data, age of roof, age of siding, ageof driveway, age of appliances, basement remodel data, square footagedata, number of bedrooms, number of bathrooms, flood or water damagedata, neighborhood crime score, proximity to public transportation,proximity to airport, proximity to major metropolitan area, proximity torecreation, school district data, fire or flood claims in neighborhood,building materials data for new construction, and/or repairs data. Basedupon an analysis of the various weights, the machine learning algorithmsmay determine that the real estate property is mortgage ready.

In other aspects, the method 700 may include updating, at the memory andaccording to an interval of time, the appraisal value based upon anychanges in the information about the real estate property beingmonitored. The interval of time may include one or more of real time,daily, every two weeks, monthly, every six months and yearly.

Still further, the method 700 may also include receiving, via the one ormore processors, updated or new information about the real estateproperty. The updated or new information may include one or more of realestate property list price, age, historical appraisal data, age of roof,age of siding, age of driveway, age of appliances, basement remodeldata, square footage data, number of bedrooms, number of bathrooms,flood or water damage data, neighborhood crime score, proximity topublic transportation, proximity to airport, proximity to majormetropolitan area, proximity to recreation, school district data, fireor flood claims in neighborhood, building materials data for newconstruction, and/or repairs data. Still further, the method 700 mayinclude then updating, at the memory, one or more of a block for theblockchain or the memory storage location to include the new informationabout one or more of the real estate property or the updated appraisalvalue according to an interval of time. The interval of time may againinclude one or more of real time, daily, every two weeks, monthly, everysix months and yearly. Still further, the method 700 may includetransmitting, via one or more of the processors, the updated blockchainto other nodes in a communication network.

Referring now to FIG. 8, a computer-implemented method 800 of approvinga dynamic mortgage application using one or more of a blockchain or amemory storage location is depicted. The blockchain may be theblockchain 222 of the blockchain system 200 of FIG. 1 and/or theblockchain 500 of FIG. 5. The steps of the flow diagram may be performedby the nodes, such as the nodes depicted in FIG. 3A. The method 800 mayinclude additional, fewer, or alternative actions, including thosedescribed elsewhere herein.

The method 800 may include determining, via one or more processors, suchas one or more processors of the insurance entity 14, for example, acustomer is approved for a mortgage (block 802). Determining a customeris approved for a mortgage or mortgage ready may include at least partof the method 600 depicted in FIG. 6 and described above. Moregenerally, determining the customer is approved for a mortgage ormortgage ready may include identifying and accessing one or more of ablockchain or a memory storage location using a customer identificationnumber to retrieve information about the customer and relative to anapproval of a mortgage (see, e.g., blocks 606 and 608 of FIG. 6).

The method 800 further may include determining, again via the one ormore processors, a real estate property is mortgage ready (block 804).Determining a real estate property is mortgage ready may include atleast part of the method 700 depicted in FIG. 7 and described above.More generally, determining the real estate property is mortgage readymay include identifying one or more of a blockchain or memory storagelocation using a real estate property identification number andaccessing one or more of the blockchain or the memory storage locationto retrieve information about the real estate property (e.g., blocks704, 706 of FIG. 7). The method 700 may also include calculating anappraisal value of the real estate property based upon the informationabout the real estate property accessed from the blockchain, comparingthe calculated appraisal value for the real estate property with a listprice of the real estate property accessed from the blockchain, andindicating the real estate property is mortgage ready when the appraisalvalue is equal to, or exceeds, the list price (see, e.g., blocks 710,712 and 716 of FIG. 7).

After it is determined the customer is approved for a mortgage and thereal estate property is mortgage ready, the method 800 further mayinclude comparing, via the one or more processors, such as the one ormore processors of the insurance entity 14, a calculated amount thecustomer is approved for a mortgage with the calculated appraisal valueof the real estate property (block 806). More specifically, the one ormore processors determine if the amount the customer is approved for amortgage is equal to, or exceeds, the calculated appraisal value of thereal estate property (block 808). If yes, the one or more processorsapproves a mortgage application of the customer for the requested realestate property that is mortgage ready (block 810). The method may thenfurther include updating, at the memory, one or more of a block for theblockchain or the memory storage location to indicate the customermortgage application for the requested real estate property is approved(block 812).

However, if the amount the customer is approved for a mortgage does notequal, or exceed, the calculated appraisal value of the real estateproperty, the one or more processors may indicate the mortgageapplication of the customer for the requested real estate property isnot approved (block 814). In one example, the method may further includeupdating, at the memory, a block for the blockchain to indicate thecustomer mortgage application for the requested property is notapproved.

In some aspects, the method 800 of FIG. 8 may further includeidentifying, via the one or more processors, a county blockchainassociated with the real estate property requested or of interest, suchas the blockchain system 21 of the computing system 20 of the countyentity in FIG. 1. In this example, the county blockchain may beidentified using the PIN and/or MLS number and accessed, at a memorycoupled to the one or more processors, corresponding to the PIN and/orMLS number to retrieve information about the real estate property. Suchinformation may include one or more of proof of a title search or proofof lien free title.

In other aspects, the method 800 may further include offering, via theone or more processors, a quote for one or more of homeowner's insuranceand mortgage insurance for the requested real estate property based uponthe calculated appraisal value. Said another way, the method 800 mayinclude generating, via the one or more processors, one or more of ahomeowner's insurance quote or a mortgage insurance quote for therequested real estate property based upon the appraisal value, which wascalculated from information accessed in the blockchain. The method 800may still further include monitoring, via the one or more processors,one or more of the retrieved information about the customer from theblockchain or the retrieved information about the real estate propertyfrom the blockchain according to an interval of time, such as real time.

The method 800 may also include updating, at the memory, one or more ofa block or the blockchain or a memory storage location to include anynew information about the customer or any new information about the realestate property identified while monitoring the information. The method800 may still further include updating, at the memory, the blockchain toinclude and/or indicate one or more of the calculated amount thecustomer is approved for a mortgage, the calculated appraisal value ofthe real estate property requested, or a status of the one or more ofthe customer or the real estate property as mortgage ready.

In view of the foregoing, one of ordinary skill in the art will at leastappreciate the following advantages of one or more of the systems andmethods 600, 700, 800. For example, the foregoing methods 600, 700, 800enable a mortgage to be processed at least within three to seven days, aconsiderably shorter period of time than the traditional 30 days or morefor conventional mortgages. In addition, because the informationrelative to customers determined to be mortgage ready and the realestate properties determined to be mortgage ready is continuouslyupdated, the customer may decide at any point that he or she is ready tocomplete a mortgage application for a particular real estate property,for example, and the work needed for the customer to be approved for themortgage is already done and updated, or already substantially done.

Moreover, by using one or more of a private, internal blockchain of theinsurance entity 14 (FIG. 1) or a memory storage location, the insuranceentity 14, such as an insurance provider, is able to market its productsas having mortgage ready advantages. Said another way, for customersalready having insurance products, such as one or more of homeowner'sinsurance, life insurance, renter's insurance, or auto insurance withthe insurance entity 14, such customers may enjoy benefits of havinginformation relative to both the customer and/or the real estateproperty being continuously updated to the blockchain. As a result, theinsurance entity 14, for example, is able to provide mortgage readystatus for one or more of the customer or the real estate property,which may enable the customer to close a property within three days. Forexample, this mortgage ready status may enable the customer to buy areal estate property, e.g., a house, and sell their real estate propertyinsured by the insurance entity 14, for example, at a significantlyfaster rate than using another vendor or conventional methods.

Further, by using the blockchain, such an internal blockchain system 200of the insurance entity 14, for at least the methods 600-800 describedabove, it is simpler and easier for customers desiring to be preapprovedfor a mortgage and/or approved for a mortgage application for a realestate property to provide information for the same. This is at leastbecause such information is pre-populated and/or included and/oraccessible on the blockchain. Said another way, there is low customereffort and a high degree of automation for customers desiring to beapproved for a mortgage using the blockchain of the insurance entity 14,for example. Because the blockchain essentially includes a digitalidentity for each of the customer and the real estate properties, asdescribed above, and the digital identity, e.g., information about eachof the customer and real estate property, is continuously updated withaccurate information, there is a significantly faster mortgage andappraisal process than conventional processes. This also allows thecustomer to be approved for a mortgage application directed to aparticular real estate property, for example, at a significantly reducedperiod of time than conventional time periods for mortgage applications,revolutionizing conventional mortgage processes.

Moreover, if the customer's current real estate property, which thecustomer desired to sell, is insured by the insurance entity 14 usingthe blockchain for information about the real estate property, forexample, the customer can market the real estate property as capable ofbeing sold, e.g., closed, within 3 to 7 days. This is an extremelydesirable period of time for many entities, including, but not limitedto, the real estate property buyer, the lender or bank entity, and theinsurance entity, such as the insurance provider.

Still further, the information about the real estate propertiescollected and updated to the blockchain is significantly more detailedand accurate compared to information about real estate propertiescurrently existing in the mortgage industry. As a result, more accuratereal estate transactions and insurance offers for the real estateproperties, for example, can occur.

As one of ordinary skill in the art will further appreciate, many of theforegoing advantages, in whole or part, are also provided by thefollowing other exemplary methods of the present disclosure.

Exemplary Methods of Continuously Monitoring and Updating Mortgage ReadyData

Referring now to FIG. 9, a computer-implemented method 900 of using oneor more of a blockchain or a memory storage location to continuouslymonitor and update information about a customer approved for a mortgage,such as a mortgage ready customer, is depicted. The method 900 mayinclude monitoring, via the one or more processors, information aboutthe customer accessed from one or more of the blockchain or the memorystorage location corresponding to an identification number of thecustomer, such as the customer identification number (block 902). Theinformation about the customer is information used to determine acustomer is approved for a mortgage and includes one or more of customerage, marital status, homeowner status, income level, occupation,finances or income, insurance status, education level, employmentstatus, telematics data, credit score data, deposit account data fordown payment, and current pay stub data and the like.

The method 900 may further include receiving, via the one or moreprocessors, new information, such as new information accessed from oneor more of the blockchain or the memory storage location, about thecustomer (block 904). The new information is used to determine thecustomer is approved for a mortgage and includes one or more of customerage, marital status, homeowner status, income level, occupation,finances or income, insurance status, education level, employmentstatus, telematics data, credit score data, deposit account data fordown payment, and current pay stub data, for example. In some aspects,the one or more processors may then update, at the memory, theblockchain or the memory storage location to include the new informationabout the customer (block 906).

The method 900 further may include verifying, via the one or moreprocessors, the new information continues to meet minimum qualificationsfor maintaining the status of the customer as approved for the mortgage,e.g., maintaining the status of the customer as mortgage ready (block908). In one example, the method may further include validating, via theone or more processors, the status of the customer as approved for themortgage when the new information meets the minimum qualifications. Theminimum qualifications include maintaining a predetermined level oramount of money in a designated deposit account for a down payment onthe real estate property and providing an updated pay stub one of everytwo week period of time, bi-monthly, or monthly indicating theemployment status is employed.

In addition, the method 900 further may include recalculating, via theone or more processors, an amount the customer is approved for amortgage based upon the new information received, such as newinformation accessed from the blockchain (block 910). The method maythen further include updating, at the memory, one or more of theblockchain or the memory storage location to include the recalculatedamount the customer is approved for the mortgage (block 912). After oneor more of the blockchain or the memory storage location is updated(block 912), the one or more processors continue to monitor theinformation about the customer accessed from one or more of theblockchain (block 902) or the memory storage location. In some aspects,the method 900 may further include transmitting, via the one or moreprocessors, the updated blockchain information to other nodes in acommunication network.

Referring now to FIG. 10, a computer-implemented method 1000 of usingone or more of a blockchain or a memory storage location to continuouslyupdate information about a real estate property identified as mortgageready is depicted. The real estate property is associated with one ormore of a real estate property identification number (PIN) and/or amultiple listing service (MLS) number, for example. The method 1000 mayinclude monitoring, via the one or more processors, informationcorresponding to the PIN and/or MLS number accessed from one or more ofthe blockchain (block 1002) or the memory storage location. Theinformation is the information used to determine if the real estateproperty is mortgage ready and includes one or more of real estateproperty age, historical appraisal data, age of roof, age of siding, ageof driveway, age of appliances, basement remodel data, square footagedata, number of bathrooms, number of bedrooms, flood or water damagedata, neighborhood crime score, proximity to public transportation,proximity to the airport, proximity to major metropolitan area,proximity to recreation, school district data, fire or flood claims inthe neighborhood, building materials data for new construction, and/orrepairs data.

The method 1000 further may include identifying, via the one or moreprocessors, new information about the real estate property, such as newinformation accessed from one or more of the blockchain (block 1004) orthe memory storage location. The new information includes any of theforegoing information used to determine the real estate property ismortgage ready listed above. The method 1000 may further includeupdating, at the memory, one or more of a block for the blockchain orthe memory storage location, to include the new information about thereal estate property (block 1006).

The method 1000 may still further include verifying, via the one or moreprocessors, that the information continues to meet minimumqualifications for maintaining the status of the real estate property asmortgage ready (block 1008). In some aspects, the minimum qualificationsfor maintaining the status of the real estate property as mortgage readyinclude having a title free of any liens and having an absence of anyinsurance claims exceeding a predetermined threshold. The predeterminedthreshold may include one of $2000, $5000, $10,000 or other thresholddetermined by an entity, such as the insurance entity 14, as critical tomaintaining the status as mortgage ready. The minimum qualifications mayfurther include maintaining the status of the real estate property inone or more of a no flood zone, a no hurricane zone, or a no earthquakezone.

The method 1000 may also include recalculating, via the one or moreprocessors, the appraisal value for the real estate property based uponone or more of the new information received or the updated informationfrom the blockchain (block 1010). In some aspects, the method 1000further may include updating, at the memory, one or more of a block forthe blockchain or the memory storage location to include therecalculated amount (block 1012).

In still further aspects, the method 1000 may include comparing, via theone or more processors, the recalculated appraisal value with a listprice accessed from one or more of the blockchain or the memory storagelocation according to an interval of time, such as real time, as definedabove. In addition, the method 1000 may still further includeindicating, via the one or more processors, the real estate property ismortgage ready when the recalculated appraisal value meets, or exceeds,the list price. In a similar manner, the method 1000 may still furtherinclude indicating, via the one or more processors, the real estateproperty is not mortgage ready when the recalculated appraisal value isbelow the list price.

Exemplary Methods of Identifying Multiple Mortgage Ready PropertiesBased Upon Customer Input

Referring now to FIG. 11, a computer-implemented method 1100 ofidentifying multiple mortgage ready properties using one or more of ablockchain or memory storage location is depicted. As in previousaspects of the present disclosure, each mortgage ready property may beassociated with a real estate property identification number (PIN)and/or a multiple listing service (MLS) number. According to someaspects, the method may include receiving, via one or more processors,information from a customer approved for a mortgage about preferencesfor a real estate property (block 1102). In some examples, theinformation includes customer preferences for one or more of real estateproperty list price, age, historical appraisal data, age of roof, age ofsiding, age of driveway, age of appliances, basement remodel data,square footage data, number of bathrooms, number of bedrooms, flood orwater damage, neighborhood crime score, proximity to publictransportation, proximity to airport, proximity to major metropolitanarea, proximity to recreation, school district data, fire or floodclaims in neighborhood, building materials for new construction, repairsdata, and price range.

The method 1100 may further include identifying, via one or moreprocessors, from one or more of a blockchain or a memory storagelocation a plurality of mortgage ready real estate properties meeting atleast one or one or more of the customer preferences informationreceived by the customer (block 1104). In addition, the method mayfurther include transmitting, via the one or more processors, theplurality of real estate properties meeting the customer preferencesinformation to the customer (block 1106) approved for a mortgage. In yetother examples, the method 1100 includes verifying, via the one or moreprocessors, from one or more of a blockchain or the memory storagelocation associated with the customer that the customer associated withthe real estate property preference information is approved for amortgage and accessing, at a memory, an amount in which the customer isapproved for the mortgage.

The method 1100 may further include receiving, via the one or moreprocessors, a request from the customer for a mortgage loan for one ofthe real estate properties meeting the customer preferences information.In addition, the method 1100 may further include comparing, via the oneor more processors, the amount in which the customer is approved for amortgage loan with an appraisal value of the requested real estateproperty accessed from one or more of the blockchain or the memorystorage location. In some examples, the method 1100 may further includecalculating, via the one or more processors, a required down paymentamount based on the appraisal value of the requested real estateproperty, for example. In addition, the method may include comparing,via the one or more processors, the required down payment amount with adeposit account value of the customer accessed from one or more of thememory storage location or the blockchain.

The method 1100 may further include approving, via the one or moreprocessors, a mortgage application of the customer for the requestedreal estate property when the amount the customer is approved for themortgage loan exceeds the appraisal value of a property selected fromthe plurality of mortgage ready properties identified as meeting one ormore of the customer's preferences (block 1108). In some examples,approving, via the one or more processors, the mortgage application ofthe customer for the requested mortgage ready real estate propertyincludes indicating, via the one or more processors, a deposit accountvalue of the customer (accessed from one or more of the memory storagelocation or blockchain) meets, or exceeds, the down payment amount forthe requested real estate property.

The method 1100 may still further include generating, via the one ormore processors, an offer for homeowner's insurance quote or mortgageinsurance quote based upon the identified mortgage ready property (block1110). Still further, the method 1100 may include transmitting, via theone or more processors, one or more quotes to the customer providing thepreferences about the real estate properties for review and approval(block 1112).

In other aspects, the method 1100 may include updating, via the one ormore processors, at least one real estate property from the plurality ofreal estate properties meeting the customer preferences informationaccording to an interval of time, such as in real time.

Exemplary Method of Incentivizing/Rating Agents Based Upon MortgageReady Customer and Real Estate Property Information

Referring now to FIG. 12, a computer-implemented method 1200 ofincentivizing an insurance agent to update one or more of a blockchainor a memory storage location is depicted. The method 1200 may includereceiving, via one or more processors, one or more of a message or asignal indicating an agent updated one or more of a blockchain or amemory storage location with mortgage ready information about thecustomer or the real estate property (block 1202). The method mayfurther include increasing, via the one or more processors and accordingto an interval of time, a score of the agent for at least one item ofinformation about one or more of the customer or the real estateproperty that was updated to one or more of the blockchain (block 1204)or memory storage location. The interval of time may include one or moreof real time, daily, bi-weekly, monthly, quarterly, bi-yearly, orannually. The method 1200 may further include calculating, via the oneor more processors, an agent rating based upon the score of the agent(block 1206). In one example, the agent rating for updating informationabout the customer or the real estate property may include one ofexcellent, very good, average, below average, and poor. The agent ratingmay be used to compute one or more of compensation or bonus of theagent, for example. The method 1200 may still further include updating,at the memory, one or more of the blockchain or memory storage location,such as by creating a new block to include the calculated insuranceagent rating relative to an identified insurance agent (block 1208).

According to some aspects, receiving a message indicating an agentupdated one or more of a blockchain or memory storage location withinformation about the customer may include receiving information aboutthe customer that includes one or more of customer age, marital status,homeowner status, income level, occupation, finances or income,insurance status, education level, employment status, telematics data,credit score data, deposit account data for down payment, and currentpayment stub data. In addition, increasing a score of the agent for atleast one item of information about the customer may include increasingthe score of the agent for each item of information about the customerupdated to one or more of the blockchain or the memory storage locationcorresponding to the customer.

According to still other aspects, receiving a message indicating anagent updated one or more of a blockchain or a memory storage locationwith information about the real estate property includes receivinginformation about the real estate property that includes one or more ofreal estate property age, historical appraisal data, age of roof, age ofsiding, age of driveway, age of one or more appliances, basement remodeldata, square footage data, number of bathrooms and/or bedrooms, flood orwater damage data, neighborhood crime score, proximity to publictransportation, proximity to airport, proximity to major metropolitanarea, proximity to recreation, school district data, fire or floodclaims in neighborhood, building materials data for new construction, orrepairs data. In addition, increasing a score of the agent for at leastone item of information updated to one or more of the blockchain or thememory storage location may include increasing the score of the agentfor each item of information about one or more of the real estateproperty or the customer updated to the blockchain.

Additional “Mortgage Ready” Embodiments

Some of the present embodiments employ blockchain technology. Otherembodiments of the present disclosure may not employ blockchaintechnologies or techniques, but employ other computer/computingtechnologies. For instance, machine learning algorithms or artificialintelligence techniques may, or may not, be utilized.

In one aspect, a computer-implemented method of determining a customeris approved for a mortgage (or mortgage ready) may be provided. Themethod may include (1) receiving, at one or more processors, a requestfor a mortgage associated with a customer identification number; (2)identifying, via the one or more processors, a computer or memory file,or memory storage location (or computer folder, or memory location)associated with the customer, the customer's computer file or memorystorage location may be identified using the customer identificationnumber; (3) accessing, at a memory coupled to the one or moreprocessors, the computer file or memory storage location correspondingto the customer identification number to retrieve information about thecustomer, the information including one or more of customer age, maritalstatus, homeowner status, income level, occupation, finances or income,insurance status, education level, employment status, telematics data,credit score data, deposit account data for down payment, and currentpayment stub data; (4) verifying, via the one or more processors, noincreased risk event occurred, the increased risk event including one ormore of a decrease in the deposit account data for down payment, adeclaration of bankruptcy, a decrease in credit score, an unemploymentclaim, or old or expired pay stub data; and/or (5) calculating, via theone or more processors, an amount the customer is approved for amortgage loan based upon the retrieved information about the customerand indicating, via the one or more processors, the customer is mortgageready, reducing the processing time for a mortgage approval. The methodmay include additional, less, or alternate actions, including thatdiscussed elsewhere herein.

In another aspect, a computer-implemented method of determining a realestate property is mortgage ready may be provided. The method mayinclude (1) receiving, at one or more processors, a request for anappraisal associated with one or more of a real estate propertyidentification number (PIN) and/or a multiple listing service (MLS)number; (2) identifying, via the one or more processors, a computer fileor memory location associated with the real estate property, the realestate property's computer file or memory location may be identifiedusing the PIN and/or MLS number; (3) accessing, at a memory coupled tothe one or more processors, the computer file or memory locationcorresponding to the PIN and/or MLS number to retrieve information aboutthe real estate property, the information including one or more of listprice, real estate property age, historical appraisal data, age of roof,age of siding, age of driveway, age of one or more appliances, basementremodel data, square footage data, number of bathrooms, number ofbedrooms, flood or water damage data, neighborhood crime score,proximity to public transportation, proximity to airport, proximity tomajor metropolitan area, proximity to recreation, school district data,fire or flood claims in neighborhood, building materials data for newconstruction, repairs data; (4) verifying, via the one or moreprocessors, no increased risk event occurred, the increased risk eventincluding one or more of an indication a claim for damages was filed orthe property is in one or more of a hurricane zone, a flood zone, or anearthquake zone; (5) calculating, via the one or more processors, anappraisal value for the real estate property based upon the retrievedinformation about the real estate property from the computer file ormemory location; (6) comparing, via the one or more processors, thecalculated appraisal value with the list price accessed from thecomputer file or memory location corresponding to the PIN and/or MLSnumber; and/or (7) indicating, via the one or more processors, the realestate property is mortgage ready when the calculated appraisal value isequal to, or exceeds, the list price value. The method may includeadditional, less, or alternate actions, including those discussedelsewhere herein.

In another aspect, a computer-implemented method of approving a dynamicmortgage application may be provided. The method may include (1)determining, via one or more processors, a customer is approved for amortgage, including calculating, via the one or more processors, anamount in which the customer is approved for a mortgage loan based uponthe information about the customer retrieved from a computer file ormemory location/address; (2) determining, via one or more processors, areal estate property is mortgage ready, including calculating, via theone or more processors, an appraisal value for the real estate propertybased upon the information about the real property retrieved from thecomputer file or memory location/address (such as by using a machinelearning or artificial intelligence algorithm); (3) comparing, via theone or more processors, the calculated amount the customer is approvedfor a mortgage loan with the calculated appraisal value of the realestate property; and/or (4) approving the mortgage application of thecustomer for the real estate property when the calculated amount thecustomer is approved for the mortgage loan meets, or exceeds, thecalculated appraisal value of the real estate property, reducing aprocessing time and closing time of the mortgage. The method may includeadditional, less, or alternate actions, including those discussedelsewhere herein.

In another aspect, a computer-implemented method of continuouslyupdating information about a customer approved for a mortgage may beprovided. The customer may be associated with a customer identificationnumber, and the method may include: (1) monitoring, via one or moreprocessors, information accessed from a computer file and/or memorylocation/address corresponding to the customer identification number,the information used to determine the customer is approved for amortgage and including one or more of customer age, marital status,homeowner status, income level, occupation, finances or income,insurance status, education level, employment status, telematics data,credit score data, deposit account data for down payment, and currentpayment stub data; (2) receiving, at the one or more processors, newinformation about the customer, the new information used to determinethe customer is approved for a mortgage and including one or more ofcustomer age, marital status, homeowner status, income level,occupation, finances or income, insurance status, education level,employment status, telematics data, credit score data, deposit accountdata for down payment, and current payment stub data; (3) updating, at amemory coupled to the one or more processors, the computer file and/ormemory location/address to include the new information; and/or (4)recalculating, via the one or more processors, the amount in which thecustomer is approved for a mortgage based upon the new informationreceived. The method may include additional, less, or alternate actions,including those discussed elsewhere herein.

In another aspect, a computer-implemented method of identifying multiplemortgage ready properties using computer technology and/or machinelearning algorithms or artificial intelligence may be provided. Eachmortgage ready property may be associated with a property identificationnumber (PIN) and/or a multiple listing service (MLS) number. The methodmay include (1) receiving, at one or more processors, information from acustomer approved for a mortgage about preferences for a real estateproperty, the information including customer preference for one or moreof real estate property list price, age, historical appraisal data, ageof roof, age of siding, age of driveway, age of appliances, basementremodel data, square footage data, number of bathrooms, number ofbedrooms, flood or water damage, neighborhood crime score, proximity topublic transportation, proximity to airport, proximity to majormetropolitan area, proximity to recreation, school district data, fireor flood claims in neighborhood, building materials for newconstruction, repairs data, and price range; (2) accessing, at a memorycoupled to the one or more processors, a computer file and/or memorylocation/address to retrieve a plurality of mortgage ready real estateproperties meeting one or more of the customer preferences information;and/or (3) transmitting, via the one or more processors, the pluralityof real estate properties meeting one or more of the customerpreferences information to the customer. The method may includeadditional, less, or alternate actions, including those discussedelsewhere herein.

In another aspect, a computer-implemented method of incentivizing aninsurance agent to update a computer file and/or memory location/addressmay be provided. The method may include (1) receiving, at one or moreprocessors, a message indicating an agent updated a computer file and/ormemory location/address with information about a customer or a realestate property; (2) increasing, via the one or more processors andaccording to an interval of time, a score of the agent for at least oneitem of information about one or more of the customer or the real estateproperty updated to the computer file and/or memory location/address,the interval of time including one or more of real time, daily, weekly,bi-weekly, monthly, or quarterly; and/or (3) calculating, via the one ormore processors, an agent rating based upon the score of the agent, theagent rating used to compute one or more of compensation or bonus of theagent. The method may include additional, less, or alternate actions,including those discussed elsewhere herein.

Exemplary Computing Device of System and Method of Approving a DynamicMortgage

Referring now to FIG. 13, a front view of an exemplary computing device12-1 of the system and method of approving a dynamic mortgageapplication of FIGS. 1A and 1B is depicted. While the computing device12-1 is depicted, one of ordinary skill in the art will appreciate thatany other computing device of FIGS. 1A and 1B, for example, disclosed inthe foregoing description may alternatively be used and still fallwithin the scope of the present disclosure. In this example, theexemplary computing device 12-1 is a smart phone, but may alternativelyinclude a tablet, a personal computer, a laptop, an iPad, a Kindle orany other type of e-reader, or other electronic device. An applicationhaving the icon 1202 associated with a mortgage ready applicationcapable of being downloaded to the exemplary computing device 12-1 isdepicted.

Upon initiating the application having the icon 1202, a display 1204 ofthe exemplary computing device 12-1 may initially list a plurality ofselections for a user or a customer. The plurality of selections includea Get MortgageReady button or touch screen area 1206, a Find A Homebutton or touch screen area 1208, a Buy A Home button or touch screenarea 1210, a Get Home Insurance button or touch screen area 1212, a LoanRates button or touch screen area 1214, a Review Loan Amount button ortouch screen area 1216, a Find An Agent button or touch screen area1218, and Questions button or touch screen area 1220.

Upon selection of the Get MortgageReady button or touch screen area 1206by a customer, for example, a verification of identity prompt for thecustomer is displayed, as depicted in FIG. 14. Said another way, FIG. 14depicts the exemplary computing device 12-1 displaying prompts forinformation relative to verifying an identity of the customer. In oneexample, the prompts displayed on the computing device 12-1 uponselection of the Get MortgageReady button or touch screen area 1206includes a Request to Enter a Zip Code prompt 1230 and a Request toEnter Last Four Digits of SS # prompt 1232.

Upon entering such data into each of the corresponding prompts 1230,1232, the exemplary computing device 12-1 displays bank accountinformation corresponding to the identified customer, as depicted inFIG. 15. More specifically, and in one example, after the datacorresponding to prompts 1230 and 1232 is entered by the customer, theexemplary computing device 12-1 transmits the data, via one or moretransmitters associated with the computing device 12-1, to the computingdevice 14 (FIGS. 1A and 1B) associated with the insurance entity, forexample, in real time. The computing device 14 associated with theinsurance entity then accesses one or more of the blockchain system 200,for example, or a memory storage location (e.g., FIG. 1B) correspondingto a customer identification number of the identified customer toretrieve information about the customer, such as financial information.

In one example, the financial information includes bank accountinformation from the insurance entity bank. The financial informationretrieved about the customer, such as bank account information and loanproducts, is then transmitted to and listed on the display 1204 of thecomputing device 12-1, as depicted in FIG. 15.

In one example, deposit account information about the customer isprovided in an area 1236 of the display 1204, and loan productinformation, such as current mortgage information, is provided inanother area 1238 of the display 1204, as also depicted in FIG. 15. Ofcourse, more or fewer bank accounts and/or loan products mayalternatively and/or additionally be displayed depending upon thecustomer information and still fall within the scope of the presentdisclosure.

In addition to the customer's financial information, one or more promptsmay also be displayed on the display 1204. In one example, the promptsmay relate to requests for any additional accounts or products withother banks different from the computing system 14 of the insuranceentity, for example. As depicted in FIG. 15, there may be another username prompt 1240 and a password prompt 1242 associated with the usernamecorresponding to a bank account or product with a third party differentthan the insurance entity. Additional data relative to such other bankaccounts and/or products may then be accessed from one or more of theblockchain 200 or memory storage location corresponding the customer andused to calculate an amount the customer is approved for a mortgage, asexplained more below.

Referring now to FIG. 16, after all of the customer information relativeto the mortgage application has been accessed from one or more of ablockchain or memory storage location associated with the customer, anamount the customer is approved for the mortgage may then be calculated.In one example, information is accessed and retrieved from a memorystorage location or a blockchain system of a third party, such asFinLocker or another entity having credit score information relative tothe customer or information about the customer relative to underwritinga loan. As is understood from this description, and explained in detailabove, calculating the amount the customer is approved for the mortgageis based upon the information retrieved about the customer relative tomortgage approval. The calculated amount the customer is approved for amortgage is then transmitted to the computing unit 12-1 and displayed onthe display 1204. In this example, both a personalized message 1244indicating the customer is “mortgage ready” and/or approved for amortgage and the calculated amount the customer is approved for themortgage 1246 are displayed on the display 1204.

In another example, an additional prompt 1248 relative to finding a homeis provided on the display 1204. If the customer is interested inreviewing homes for sale at that time, the customer may actuate the yesbutton 1250 to review a list of mortgage ready homes having an appraisalvalue equal to, less than, or within a range of the amount the customeris approved for the mortgage. Alternatively, if the customer is notinterested in finding homes for sale at that time, the customer mayactuate the No button 1252 to end the mortgage ready application on thecomputing system 12-1 of the customer.

Referring now to FIG. 17, when the customer actuates the yes button 1250(FIG. 15), a listing of real estate properties 1254 determined to bemortgage ready and having a calculated appraisal value meeting, lessthan, or within a range of the amount the customer is approved for amortgage is displayed. In this listing of real estate properties 1254,the address of each real estate property and corresponding appraisalvalue may be displayed, as depicted in FIG. 17. In another example, amap 1256 depicting the location of each of the real estate propertiesprovided in the listing of real estate properties 1254 may also bedisplayed, depicting the location of each real estate property relativeto the other real estate properties in the listing 1254.

In addition, in one example, pins 1258 associated with a real estateproperty displayed on a map 1256 of the display 1204 may be color codedto help indicate a status. More specifically, pins 1258 having the colorred may indicate the real estate property has mortgage ready status, andpins 1258 having the color blue may indicate the real estate propertydoes not have mortgage ready status. Further, in another example, realestate properties that are for sale and have a listing value that isgreater than the calculated amount the customer is approved for themortgage may be displayed in the listing of real estate properties 1254in a different color, such as the color gray. Likewise, real estateproperties in the listing 1254 having a listing value that meets or isless than the calculated amount the customer is approved for themortgage may be displayed in the color green.

Of course, one of ordinary skill in the art will understand that variousother colors, shapes or icons may alternatively be used to code suchfeatures of the real estate properties, for example, and still fallwithin the scope of the present disclosure. Moreover, the listing ofreal estate properties 1254 may be accessed from a third party entity 23(e.g., FIG. 1B), which may be one or more of an MLS service, Zillow, orother real estate property service having such information.

One of ordinary skill in the art will further appreciate the followingbenefits of the systems and methods described herein. For example, withthe mortgage ready application and methods, part of which is depicted inFIG. 13, customers are continuously in an approved status, up to asupported loan amount. In addition, the systems and processes of themortgage ready application allow the customer's information to beregularly refreshed and/or updated, which is then used to constantlyupdate the calculated amount the customer is approved for a mortgage. Inaddition, when a customer has found a specific real estate property,MortgageReady application is able to seamlessly populate a 1003application to formally complete the loan process. As a result, thecustomers will experience the fastest, simplest approval process in theindustry, all with confidence that they are already approved.

Further, the real estate properties currently and formerly insured bythe insurance entity also benefit as they are ready to be purchased uponreceiving mortgage ready status, as described herein. Leveraging andaccessing existing insurance entity property data, public data and titleinformation from one or more of any of the blockchain systems or memorystorage locations described above, such real estate properties arequalified for an accelerated purchase. Further, the insurance entitywill capitalize on the existing data to drastically reduce the costs andtime associated with appraisals and title transfers. When a customer ofa bank affiliated with the insurance entity is purchasing aMortgageReady real estate property insured by the insurance entity, forexample, they will experience a faster, easier collateral verificationand title transfer process.

In one aspect, a computer-implemented method of matching a mortgageready customer with a mortgage ready property may be provided. Themethod may include, via one or more processors, servers, networks,and/or transceivers: (1) retrieving from a memory unit, or receiving(such as via wireless communication or data transmission over one ormore radio frequency links) customer income and/or asset information;(2) verifying an identity of a customer that is currently online, suchas via a secure network connection; (3) verifying that the customer'sincome and/or asset information is up-to-date or current, or receivingup-to-date income and/or asset information for the customer via a securenetwork connection; (4) pre-approving the customer up to a maximum loanamount based upon the current or up-to-date customer income and/or assetinformation; (5) asking or inquiring of the customer if they are readyto search available (and/or mortgage ready) properties, or otherwisereceiving an indication from the customer's mobile device that thecustomer is actively shopping properties or wants to see availableproperties; (6) if so, causing a virtual map of available properties forsale to be graphically depicted on the customer's mobile device, theproperties graphically depicted being color coded to indicate whether(i) they have list prices below the maximum loan amount that thecustomer is currently pre-approved for, and/or (ii) are mortgage ready(e.g., pre-vetted to indicate that an appraisal indicates that the houseis valued at or near the asking price). The map depicted may be centeredabout or around a current GPS location retrieved or received from thecustomer's mobile device. The method may include additional, less, oralternate actions, including those discussed elsewhere herein.

In another aspect, a computer system configured to match a mortgageready customer with a mortgage ready property may be provided. Thesystem may include one or more processors, servers, networks, and/ortransceivers configured to: (1) retrieve from a memory unit, or receive(such as via wireless communication or data transmission over one ormore radio frequency links) customer income and/or asset information;(2) verify an identity of a customer that is currently online, such asvia a secure network connection; (3) verify that the customer's incomeand/or asset information is up-to-date or current, or receive up-to-dateincome and/or asset information for the customer via a secure networkconnection; (4) pre-approve the customer up to a maximum loan amountbased upon the current or up-to-date customer income and/or assetinformation; (5) ask or inquire of the customer if they are ready tosearch available (and/or mortgage ready) properties, or otherwisereceive an indication from the customer's mobile device that thecustomer is actively shopping properties or wants to view availableproperties; and/or (6) if so, cause a virtual map of availableproperties for sale to be graphically depicted on the customer's mobiledevice, the properties graphically depicted being color coded toindicate whether (i) they have list prices below the maximum loan amountthat the customer is currently pre-approved for, and/or (ii) aremortgage ready (e.g., pre-vetted to indicate that an appraisal indicatesthat the house is valued at or near the asking price). The map depictedmay be centered about or around a current GPS location retrieved orreceived from the customer's mobile device. The system may includeadditional, less, or alternate functionality, including that discussedelsewhere herein.

In another aspect, a graphical user interface (GUI) for graphicallyrepresenting or virtually depicting mortgage ready properties may beprovided. The GUI may include (1) a map portion showing or depictingproperties for sale, such as via icons, the properties or representativeicons being color coded. The GUI may utilize color coding, i.e., a firstand second color, within the map portion, such as the first color beingassociated with properties that are (i) mortgage ready, and/or (ii)within a purchase price amount that the customer is approved for; andthe second color being associated with properties that are (i) notmortgage ready (i.e., not pre-vetted/inspected/appraised), and/or (ii)have list prices above an approved max purchase price for the customer.The GUI may also include (2) a list price portion listing (a) addresses,and (b) list prices for the properties shown in the map portion. As aresult, matching mortgage ready customers with mortgage ready propertiesis facilitated and the customer experience enhanced.

ADDITIONAL CONSIDERATIONS

The following additional considerations apply to the foregoingdiscussion. Throughout this specification, plural instances mayimplement components, operations, or structures described as a singleinstance. Although individual operations of one or more methods areillustrated and described as separate operations, one or more of theindividual operations may be performed concurrently, and nothingrequires that the operations be performed in the order illustrated.Structures and functionality presented as separate components in exampleconfigurations may be implemented as a combined structure or component.Similarly, structures and functionality presented as a single componentmay be implemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Discussions herein referring to an “appraiser,” “inspector,” “adjuster,”“claim representative” or the like are non-limiting. One skilled in theart will appreciate that any user associated with an insurance companyor an insurance function may utilize one or more of the devices,systems, and methods disclosed in the foregoing description. One skilledin the art will further realize that any reference to a specific jobtitle or role does not limit the disclosed devices, systems, or methods,or the type of user of said devices, systems, or methods.

Certain implementations are described herein as including logic or anumber of components, modules, or mechanisms. Modules may constituteeither software modules (e.g., code implemented on a tangible,non-transitory machine-readable medium such as RAM, ROM, flash memory ofa computer, hard disk drive, optical disk drive, tape drive, etc.) orhardware modules (e.g., an integrated circuit, an application-specificintegrated circuit (ASIC), a field programmable logic array(FPLA)/field-programmable gate array (FPGA), etc.). A hardware module isa tangible unit capable of performing certain operations and may beconfigured or arranged in a certain manner. In exemplaryimplementations, one or more computer systems (e.g., a standalone,client or server computer system) or one or more hardware modules of acomputer system (e.g., a processor or a group of processors) may beconfigured by software (e.g., an application or application portion) asa hardware module that operates to perform certain operations asdescribed herein.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine (e.g., a computer) that manipulates or transformsdata represented as physical (e.g., electronic, magnetic, or optical)quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation.

As used herein any reference to “one implementation,” “one embodiment,”“an implementation,” or “an embodiment” means that a particular element,feature, structure, or characteristic described in connection with theimplementation is included in at least one implementation. Theappearances of the phrase “in one implementation” or “in one embodiment”in various places in the specification are not necessarily all referringto the same implementation.

Some implementations may be described using the expression “coupled”along with its derivatives. For example, some implementations may bedescribed using the term “coupled” to indicate that two or more elementsare in direct physical or electrical contact. The term “coupled,”however, may also mean that two or more elements are not in directcontact with each other, but yet still co-operate or interact with eachother. The implementations are not limited in this context.

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive or and not to an exclusive or. For example,a condition A or B is satisfied by any one of the following: A is true(or present) and B is false (or not present), A is false (or notpresent) and B is true (or present), and both A and B are true (orpresent).

In addition, use of the “a” or “an” are employed to describe elementsand components of the implementations herein. This is done merely forconvenience and to give a general sense of the invention. Thisdescription should be read to include one or at least one and thesingular also includes the plural unless it is obvious that it is meantotherwise.

Moreover, the patent claims at the end of this patent application arenot intended to be construed under 35 U.S.C. § 112(f) unless traditionalmeans-plus-function language is expressly recited, such as “means for”or “step for” language being explicitly recited in the claim(s). Thesystems and methods described herein are directed to an improvement tocomputer functionality, and improve the functioning of conventionalcomputers.

Upon reading this disclosure, those of skill in the art will appreciatestill additional alternative structural and functional designs for asystem and a process for inspecting a structure to estimate thecondition of a structure through the disclosed principles herein. Thus,while particular implementations and applications have been illustratedand described, it is to be understood that the disclosed implementationsare not limited to the precise construction and components disclosedherein. Various modifications, changes and variations, which will beapparent to those skilled in the art, may be made in the arrangement,operation and details of the method and apparatus disclosed hereinwithout departing from the spirit and scope defined in the appendedclaims.

We claim:
 1. A computer-implemented method of continuously updatinginformation about a customer approved for a mortgage, the customerassociated with a customer identification number and the methodcomprising: maintaining a copy of a blockchain associated with thecustomer, the blockchain including one or more blocks includingvalidated information about the customer; accessing, based at least inpart on the customer identification number, the validated information;determining, based at least in part on the validated information, anamount for which the customer is approved for a mortgage; monitoring,via one or more processors and at an interval of time, informationcorresponding to the customer identification number, the informationused to determine the customer is approved for the mortgage andincluding one or more of customer age, marital status, homeowner status,income level, occupation, finances or income, insurance status,education level, employment status, telematics data, credit score data,deposit account data for down payment, and current payment stub data;receiving, at the one or more processors and based on the monitoring,new information about the customer, the new information used todetermine the customer is approved for the mortgage and including one ormore of customer age, marital status, homeowner status, income level,occupation, finances or income, insurance status, education level,employment status, telematics data, credit score data, deposit accountdata for down payment, and current payment stub data; compiling a newblock for the blockchain including the new information, whereincompiling the new block includes computing a hash value using acryptographic hash function and assigning the hash value to the newblock; and determining, via the one or more processors, an updatedamount for which the customer is approved for the mortgage based uponthe new information.
 2. The method of claim 1, further comprisingverifying, via the one or more processors, the new information continuesto meet minimum qualifications for maintaining status of customer asapproved for a mortgage, the minimum qualifications includingmaintaining a predetermined down payment amount in a deposit account andproviding an updated pay stub indicating employment status is currentlyemployed.
 3. The method of claim 2, further comprising validating, viathe one or more processors, the status of the customer as approved forthe mortgage when the new information meets the minimum qualificationsfor maintaining the status of the customer as approved for the mortgage.4. The method of claim 1, further comprising compiling an additionalblock for the blockchain including the updated amount, wherein compilingthe additional block includes computing a second hash value using asecond cryptographic hash function and assigning the second hash valueto the additional block.
 5. The method of claim 4, further comprisingtransmitting, via the one or more processors, the updated amount orinformation about the additional block to other nodes in a communicationnetwork.
 6. The method of claim 1, where the information about thecustomer, with the customer's affirmative consent or opt-in to amortgage ready program, is continuously monitored and updated accordingto the interval of time, the interval of time including one or more ofin real time, hourly, daily or weekly.
 7. A system for continuouslyupdating information about a customer approved for a mortgage usingcomputer technology and/or machine learning algorithms or artificialintelligence, the customer associated with a customer identificationnumber record tracked by a computer file and/or memory location/address,the system comprising: a network interface configured to interface withone or more processors of an insurance entity; a memory configured tostore non-transitory computer executable instructions and configured tointerface with the one or more processors; and the one or moreprocessors configured to interface with the memory, wherein the one ormore processors are configured to execute the non-transitory computerexecutable instructions to cause the system to: maintain a copy of ablockchain associated with a customer, the blockchain including one ormore blocks including validated information about the customer; accessthe validated information; determine, based at least in part on thevalidated information, an amount for which the customer is approved fora mortgage; monitor, based at least in part on the customer beingapproved for the mortgage and at an interval of time, informationcorresponding to the customer; determine, based at least in part on themonitoring, new information about the customer; compile a new block forthe blockchain including the new information about the customer, whereincompiling the new block includes computing a hash value using acryptographic hash function and assigning the hash value to the newblock; and determine an updated amount for which the customer isapproved for the mortgage based upon the new information.
 8. The systemof claim 7, wherein the instructions, when executed, further cause theprocessor to: verify the new information continues to meet minimumqualifications for maintaining the status of the customer approved forthe mortgage.
 9. The system of claim 8, wherein the minimumqualifications for maintaining the status of the customer as approvedfor the mortgage include maintaining a predetermined down payment amountin a deposit account and providing an updated pay stub indicatingemployment status is currently employed.
 10. The system of claim 8,wherein the instructions, when executed, further cause the processor to:validate the status of the customer as approved for the mortgage whenthe new information meets the minimum qualifications for maintaining thestatus of the customer as approved for the mortgage.
 11. The system ofclaim 8, wherein the instructions, when executed, further cause theprocessor to: compile an additional block for the blockchain includingthe updated amount, wherein compiling the additional block includescomputing a second hash value using a second cryptographic hash functionand assigning the second hash value to the additional block.
 12. Thesystem of claim 7, wherein new information about the customer isinformation used to determine the customer is approved for a mortgageand includes one or more of customer age, marital status, homeownerstatus, income level, occupation, finances or income, insurance status,education level, employment status, telematics data, credit score data,deposit account data for down payment, and current payment stub data.13. A computer-implemented method comprising: maintaining a first copyof a first blockchain associated with a first customer and a second copyof a second blockchain associated with a second customer, the firstblockchain including one or more first blocks including first validatedinformation about the first customer and the second blockchain includingone or more second block including second validated information aboutthe second customer; receiving a customer identification numberassociated with a customer; accessing, based at least in part on thecustomer identification number being associated with the first customerand via one or more processors, the first validated information;determining, via the one or more processors and based at least in parton the first validated information, an amount for which the firstcustomer is approved for a mortgage; monitoring, at an interval of time,information associated with the first customer approved for themortgage; receiving, in response to the monitoring, a transactioncomprising new information about the first customer; compiling a newblock for the first blockchain including the new information about thefirst customer, wherein compiling the new block includes computing ahash value using a cryptographic hash function and assigning the hashvalue to the new block; and determining, via the one or more processorsand based at least in part on the new information, an updated amount forwhich the customer is approved for the mortgage.
 14. Thecomputer-implemented method of claim 13, further comprising: compilingan additional block for the first blockchain including the updatedamount, wherein compiling the additional block includes computing asecond hash value using a second cryptographic hash function andassigning the second hash value to the additional block.
 15. Thecomputer-implemented method of claim 13, further comprising:determining, based at least in part on the customer information and thenew information, that the customer is approved for the mortgage.
 16. Thecomputer-implemented method of claim 15, wherein the determining thatthe customer is approved for the mortgage comprises comparing the newinformation to qualifications for determining the customer is approved.17. The computer-implemented method of claim 16, wherein thequalifications include at least one of maintaining a predetermined downpayment amount in a deposit account or providing an updated pay stub.18. The computer-implemented method of claim 15, wherein the receivingthe new information is performed at a frequency, the method furthercomprising: revoking, in response to a failure to receive the newinformation at the frequency, the mortgage approval.
 19. Thecomputer-implemented method of claim 13, wherein at least one of thecustomer information or the new information comprises one or more ofcustomer age, marital status, homeowner status, income level,occupation, finances or income, insurance status, education level,employment status, telematics data, credit score data, deposit accountdata for down payment, and current payment stub data.